Introduction
Diff-in-Diff models
We will be utilizing diff-in-diff models to analyze the impacts of the New Markets Tax Credit (NMTC) and the Low Income Housing Tax Credit (LIHTC) programs as they relate to social vulnerability and economic changes in Mountain Division tracts.
Diff-In-Diff models are useful as a statistical tool to analyze the effects of a program when there is a treatment group and a group who did not receive the treatment (control group). It can be used when there are two periods, before intervention and after intervention. Since we have tracts who did receive NMTC and LIHTC dollars and tracts who did not, we can analyze the impact of these programs before and after intervention.
Dependent Variables: SVI Variables, House Price Index, Median Home Values, and Median Income
These variables were chosen as dependent variables to look at the impact of our tax programs. The social vulnerability index looks at 4 categories of interest that the CDC has determined impacts overall vulnerability of communities. It is broken down in the following categories: socioeconomic status, household characteristics, racial & ethnic minority status, and housing type/transportation. We will also be looking at economic variables. The house price index is determined by analyzing mortgage transactions. The median home value and median incomes will be collected by census data.
Independent Variables: NMTC and LIHTC Data
New Markets Tax Credits are awarded to community development entities for the purpose of investing in low income communities and recipients must meet strict criteria to be eligible, but the credits are intended to for areas with low median income and high poverty rates.
Low Income Housing Tax Credits are awarded to investors with the purpose of investing in affordable housing for renters. Again, this program is designed to improve neighborhood with low gross incomes and high poverty rates.
Library
# Load packages
library(here) # relative filepaths for reproducibility
library(rio) # read excel file from URL
library(tidyverse) # data wrangling
library(stringi) # string data wrangling
library(tidycensus) # US census data
library(ggplot2) # data visualization
library(kableExtra) # table formatting
library(scales) # palette and number formatting
library(unhcrthemes) # data visualization themes
library(ggrepel) # data visualization formatting to avoid overlapping
library(rcompanion) # data visualization of variable distribution
library(ggpubr) # data visualization of variable distribution
library(moments) # measures of skewness and kurtosis
library(tinytable) # format regression tables
library(modelsummary) # format regression tables
Load Functions
import::here( "fips_census_regions",
"load_svi_data",
"merge_svi_data",
"census_division",
"slopegraph_plot",
"census_pull",
# notice the use of here::here() that points to the .R file
# where all these R objects are created
.from = here::here("analysis/project_data_steps_knopp.R"),
.character_only = TRUE)
# Load API key, assign to TidyCensus Package
source(here::here("analysis/password.R"))
census_api_key(census_api_key)
Data
# Load NMTC AND LIHTC data sets
svi_divisional_nmtc <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_divisional_nmtc.rds")))
svi_national_nmtc <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_national_nmtc.rds")))
svi_divisional_lihtc <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_divisional_lihtc.rds")))
svi_national_lihtc <- readRDS(here::here(paste0("data/wrangling/", str_replace_all(census_division, " ", "_"), "_svi_national_lihtc.rds")))
View NMTC Data
*Divisional**
svi_divisional_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | FIPS_st | FIPS_county | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | nmtc_eligibility | pre10_nmtc_project_cnt | pre10_nmtc_dollars | pre10_nmtc_dollars_formatted | post10_nmtc_project_cnt | post10_nmtc_dollars | post10_nmtc_dollars_formatted | nmtc_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 04001942600 | 04 | 001 | 942600 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 1561 | 762 | 384 | 1150 | 1561 | 73.67072 | 0.9944 | 1 | 26 | 300 | 8.666667 | 0.6866 | 0 | 65 | 366 | 17.759563 | 0.10180 | 0 | 5 | 18 | 27.77778 | 0.19090 | 0 | 70 | 384 | 18.22917 | 0.05781 | 0 | 303 | 839 | 36.11442 | 0.9335 | 1 | 282 | 1578 | 17.87072 | 0.5921 | 0 | 153 | 9.801409 | 0.4496 | 0 | 560 | 35.87444 | 0.9044 | 1 | 240 | 1054 | 22.770398 | 0.9006 | 1 | 107 | 332 | 32.22892 | 0.9163 | 1 | 168 | 1431 | 11.740042 | 0.8831 | 1 | 1561 | 1561 | 100.00000 | 0.9989 | 1 | 762 | 0 | 0.0000000 | 0.1526 | 0 | 215 | 28.21522 | 0.9088 | 1 | 117 | 384 | 30.46875 | 0.9979 | 1 | 33 | 384 | 8.59375 | 0.7842 | 1 | 0 | 1561 | 0.000000 | 0.3955 | 0 | 3.26441 | 0.7248 | 2 | 4.0540 | 0.9853 | 4 | 0.9989 | 0.9931 | 1 | 3.2390 | 0.8004 | 3 | 11.55631 | 0.8966 | 10 | 1711 | 676 | 469 | 930 | 1711 | 54.35418 | 0.9708 | 1 | 44 | 484 | 9.090909 | 0.8539 | 1 | 32 | 456 | 7.017544 | 0.02013 | 0 | 4 | 13 | 30.76923 | 0.24630 | 0 | 36 | 469 | 7.675906 | 0.005758 | 0 | 304 | 1197 | 25.39683 | 0.9056 | 1 | 686 | 1711 | 40.09351 | 0.9973 | 1 | 229 | 13.38399 | 0.4397 | 0 | 347 | 20.28054 | 0.3788 | 0 | 245 | 1363.979 | 17.962156 | 0.68240 | 0 | 49 | 304.000 | 16.11842 | 0.5859 | 0 | 155 | 1652 | 9.382567 | 0.8951 | 1 | 1711 | 1710.980 | 100.00115 | 1.0000 | 1 | 676 | 0 | 0.0000000 | 0.1276 | 0 | 142 | 21.00592 | 0.8736 | 1 | 83 | 469 | 17.697228 | 0.9774 | 1 | 99 | 469.000 | 21.10874 | 0.9655 | 1 | 0 | 1711 | 0.0000000 | 0.2155 | 0 | 3.733358 | 0.8474 | 4 | 2.98190 | 0.7375 | 1 | 1.0000 | 0.9958 | 1 | 3.1596 | 0.7653 | 3 | 10.87486 | 0.8573 | 9 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 04001942700 | 04 | 001 | 942700 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4886 | 2757 | 1291 | 2616 | 4871 | 53.70560 | 0.9480 | 1 | 163 | 1398 | 11.659514 | 0.8577 | 1 | 102 | 1113 | 9.164421 | 0.01757 | 0 | 54 | 178 | 30.33708 | 0.22790 | 0 | 156 | 1291 | 12.08366 | 0.01652 | 0 | 1039 | 2931 | 35.44865 | 0.9303 | 1 | 1873 | 5249 | 35.68299 | 0.9436 | 1 | 688 | 14.081048 | 0.6870 | 0 | 1530 | 31.31396 | 0.7718 | 1 | 772 | 3514 | 21.969266 | 0.8839 | 1 | 246 | 939 | 26.19808 | 0.8308 | 1 | 592 | 4631 | 12.783416 | 0.8975 | 1 | 4846 | 4886 | 99.18133 | 0.9946 | 1 | 2757 | 0 | 0.0000000 | 0.1526 | 0 | 369 | 13.38411 | 0.7652 | 1 | 240 | 1291 | 18.59024 | 0.9756 | 1 | 188 | 1291 | 14.56235 | 0.9015 | 1 | 0 | 4886 | 0.000000 | 0.3955 | 0 | 3.69612 | 0.8288 | 4 | 4.0710 | 0.9870 | 4 | 0.9946 | 0.9890 | 1 | 3.1904 | 0.7848 | 3 | 11.95212 | 0.9295 | 12 | 5469 | 2222 | 1462 | 2784 | 5469 | 50.90510 | 0.9557 | 1 | 358 | 1642 | 21.802680 | 0.9925 | 1 | 114 | 1151 | 9.904431 | 0.04797 | 0 | 58 | 311 | 18.64952 | 0.09477 | 0 | 172 | 1462 | 11.764706 | 0.023990 | 0 | 852 | 3274 | 26.02321 | 0.9120 | 1 | 1856 | 5466 | 33.95536 | 0.9919 | 1 | 759 | 13.87822 | 0.4657 | 0 | 1555 | 28.43299 | 0.7739 | 1 | 706 | 3911.002 | 18.051640 | 0.68720 | 0 | 257 | 1035.000 | 24.83091 | 0.8039 | 1 | 396 | 5078 | 7.798346 | 0.8624 | 1 | 5420 | 5469.002 | 99.10401 | 0.9946 | 1 | 2222 | 0 | 0.0000000 | 0.1276 | 0 | 400 | 18.00180 | 0.8488 | 1 | 238 | 1462 | 16.279070 | 0.9710 | 1 | 175 | 1462.001 | 11.96990 | 0.8742 | 1 | 26 | 5469 | 0.4754068 | 0.6430 | 0 | 3.876090 | 0.8796 | 4 | 3.59310 | 0.9421 | 3 | 0.9946 | 0.9905 | 1 | 3.4646 | 0.8721 | 3 | 11.92839 | 0.9425 | 11 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 04001944000 | 04 | 001 | 944000 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 5958 | 2178 | 1275 | 3112 | 5958 | 52.23229 | 0.9399 | 1 | 107 | 1895 | 5.646438 | 0.4130 | 0 | 108 | 880 | 12.272727 | 0.03476 | 0 | 112 | 395 | 28.35443 | 0.19940 | 0 | 220 | 1275 | 17.25490 | 0.04955 | 0 | 1030 | 3376 | 30.50948 | 0.9015 | 1 | 2632 | 5821 | 45.21560 | 0.9873 | 1 | 472 | 7.922122 | 0.3301 | 0 | 1792 | 30.07721 | 0.7211 | 0 | 299 | 4027 | 7.424882 | 0.1343 | 0 | 272 | 979 | 27.78345 | 0.8590 | 1 | 153 | 5325 | 2.873239 | 0.6096 | 0 | 5846 | 5958 | 98.12017 | 0.9893 | 1 | 2178 | 0 | 0.0000000 | 0.1526 | 0 | 448 | 20.56933 | 0.8562 | 1 | 247 | 1275 | 19.37255 | 0.9798 | 1 | 135 | 1275 | 10.58824 | 0.8373 | 1 | 0 | 5958 | 0.000000 | 0.3955 | 0 | 3.29125 | 0.7314 | 3 | 2.6541 | 0.5792 | 1 | 0.9893 | 0.9836 | 1 | 3.2214 | 0.7946 | 3 | 10.15605 | 0.7714 | 8 | 6583 | 2464 | 1836 | 3270 | 6580 | 49.69605 | 0.9486 | 1 | 191 | 2029 | 9.413504 | 0.8663 | 1 | 89 | 1272 | 6.996855 | 0.01965 | 0 | 103 | 564 | 18.26241 | 0.09073 | 0 | 192 | 1836 | 10.457516 | 0.015550 | 0 | 753 | 4321 | 17.42652 | 0.8100 | 1 | 2993 | 6580 | 45.48632 | 0.9992 | 1 | 1034 | 15.70712 | 0.5561 | 0 | 1569 | 23.83412 | 0.5584 | 0 | 1069 | 5014.189 | 21.319499 | 0.81410 | 1 | 304 | 1237.278 | 24.57006 | 0.7989 | 1 | 141 | 6193 | 2.276764 | 0.6147 | 0 | 6436 | 6583.375 | 97.76141 | 0.9876 | 1 | 2464 | 20 | 0.8116883 | 0.3404 | 0 | 536 | 21.75325 | 0.8793 | 1 | 274 | 1836 | 14.923747 | 0.9643 | 1 | 326 | 1836.376 | 17.75235 | 0.9488 | 1 | 3 | 6583 | 0.0455719 | 0.4382 | 0 | 3.639650 | 0.8211 | 4 | 3.34220 | 0.8770 | 2 | 0.9876 | 0.9834 | 1 | 3.5710 | 0.9020 | 3 | 11.54045 | 0.9156 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 04001944100 | 04 | 001 | 944100 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4975 | 2485 | 1204 | 3251 | 4968 | 65.43881 | 0.9846 | 1 | 210 | 1254 | 16.746412 | 0.9576 | 1 | 122 | 905 | 13.480663 | 0.04383 | 0 | 91 | 299 | 30.43478 | 0.22960 | 0 | 213 | 1204 | 17.69103 | 0.05320 | 0 | 779 | 2325 | 33.50538 | 0.9203 | 1 | 1293 | 5511 | 23.46217 | 0.7705 | 1 | 344 | 6.914573 | 0.2701 | 0 | 1993 | 40.06030 | 0.9701 | 1 | 577 | 3087 | 18.691286 | 0.7799 | 1 | 278 | 893 | 31.13102 | 0.9038 | 1 | 308 | 4470 | 6.890380 | 0.7895 | 1 | 4915 | 4975 | 98.79397 | 0.9929 | 1 | 2485 | 21 | 0.8450704 | 0.3700 | 0 | 428 | 17.22334 | 0.8203 | 1 | 257 | 1204 | 21.34551 | 0.9843 | 1 | 212 | 1204 | 17.60797 | 0.9391 | 1 | 0 | 4975 | 0.000000 | 0.3955 | 0 | 3.68620 | 0.8261 | 4 | 3.7134 | 0.9528 | 4 | 0.9929 | 0.9872 | 1 | 3.5092 | 0.8926 | 3 | 11.90170 | 0.9244 | 12 | 6183 | 2379 | 1424 | 3704 | 5789 | 63.98342 | 0.9912 | 1 | 425 | 1608 | 26.430348 | 0.9954 | 1 | 132 | 1163 | 11.349957 | 0.07802 | 0 | 38 | 261 | 14.55939 | 0.06498 | 0 | 170 | 1424 | 11.938202 | 0.026300 | 0 | 862 | 3259 | 26.44983 | 0.9148 | 1 | 1320 | 6183 | 21.34886 | 0.9283 | 1 | 637 | 10.30244 | 0.2718 | 0 | 1869 | 30.22804 | 0.8396 | 1 | 626 | 3964.000 | 15.792129 | 0.57150 | 0 | 371 | 991.000 | 37.43693 | 0.9557 | 1 | 315 | 5717 | 5.509883 | 0.8021 | 1 | 5981 | 6182.998 | 96.73300 | 0.9841 | 1 | 2379 | 0 | 0.0000000 | 0.1276 | 0 | 442 | 18.57924 | 0.8550 | 1 | 379 | 1424 | 26.615168 | 0.9969 | 1 | 347 | 1424.000 | 24.36798 | 0.9758 | 1 | 394 | 6183 | 6.3723112 | 0.9380 | 1 | 3.856000 | 0.8749 | 4 | 3.44070 | 0.9070 | 3 | 0.9841 | 0.9800 | 1 | 3.8933 | 0.9609 | 4 | 12.17410 | 0.9549 | 12 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 04001944202 | 04 | 001 | 944202 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 3330 | 1463 | 897 | 1814 | 3330 | 54.47447 | 0.9514 | 1 | 345 | 1024 | 33.691406 | 0.9983 | 1 | 58 | 745 | 7.785235 | 0.01352 | 0 | 38 | 152 | 25.00000 | 0.15680 | 0 | 96 | 897 | 10.70234 | 0.01191 | 0 | 742 | 2041 | 36.35473 | 0.9351 | 1 | 1201 | 3754 | 31.99254 | 0.9089 | 1 | 366 | 10.990991 | 0.5201 | 0 | 873 | 26.21622 | 0.5389 | 0 | 573 | 2986 | 19.189551 | 0.8002 | 1 | 151 | 550 | 27.45455 | 0.8540 | 1 | 173 | 3057 | 5.659143 | 0.7527 | 1 | 3306 | 3330 | 99.27928 | 0.9948 | 1 | 1463 | 0 | 0.0000000 | 0.1526 | 0 | 355 | 24.26521 | 0.8840 | 1 | 114 | 897 | 12.70903 | 0.9435 | 1 | 257 | 897 | 28.65106 | 0.9864 | 1 | 93 | 3330 | 2.792793 | 0.8680 | 1 | 3.80561 | 0.8512 | 4 | 3.4659 | 0.8981 | 3 | 0.9948 | 0.9891 | 1 | 3.8345 | 0.9589 | 4 | 12.10081 | 0.9410 | 12 | 3507 | 1508 | 1209 | 2113 | 3507 | 60.25093 | 0.9862 | 1 | 145 | 1041 | 13.928914 | 0.9605 | 1 | 81 | 1040 | 7.788462 | 0.02620 | 0 | 26 | 169 | 15.38462 | 0.07170 | 0 | 107 | 1209 | 8.850290 | 0.008637 | 0 | 403 | 2250 | 17.91111 | 0.8195 | 1 | 1457 | 3507 | 41.54548 | 0.9985 | 1 | 390 | 11.12062 | 0.3153 | 0 | 974 | 27.77303 | 0.7446 | 0 | 114 | 2533.000 | 4.500592 | 0.01399 | 0 | 189 | 717.000 | 26.35983 | 0.8350 | 1 | 389 | 3265 | 11.914242 | 0.9273 | 1 | 3499 | 3507.000 | 99.77188 | 0.9983 | 1 | 1508 | 26 | 1.7241379 | 0.4052 | 0 | 434 | 28.77984 | 0.9188 | 1 | 98 | 1209 | 8.105873 | 0.8737 | 1 | 146 | 1209.000 | 12.07610 | 0.8761 | 1 | 0 | 3507 | 0.0000000 | 0.2155 | 0 | 3.773337 | 0.8552 | 4 | 2.83619 | 0.6678 | 2 | 0.9983 | 0.9941 | 1 | 3.2893 | 0.8112 | 3 | 10.89713 | 0.8589 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 04001944300 | 04 | 001 | 944300 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 6806 | 3308 | 1826 | 4099 | 6797 | 60.30602 | 0.9762 | 1 | 403 | 1777 | 22.678672 | 0.9858 | 1 | 154 | 1457 | 10.569664 | 0.02549 | 0 | 63 | 369 | 17.07317 | 0.08684 | 0 | 217 | 1826 | 11.88390 | 0.01536 | 0 | 1432 | 3367 | 42.53044 | 0.9623 | 1 | 2305 | 7092 | 32.50141 | 0.9160 | 1 | 746 | 10.960917 | 0.5176 | 0 | 2767 | 40.65530 | 0.9761 | 1 | 842 | 4361 | 19.307498 | 0.8041 | 1 | 357 | 1163 | 30.69647 | 0.8982 | 1 | 568 | 6178 | 9.193914 | 0.8423 | 1 | 6750 | 6806 | 99.17720 | 0.9944 | 1 | 3308 | 8 | 0.2418380 | 0.3113 | 0 | 440 | 13.30109 | 0.7638 | 1 | 404 | 1826 | 22.12486 | 0.9856 | 1 | 388 | 1826 | 21.24863 | 0.9627 | 1 | 139 | 6806 | 2.042316 | 0.8458 | 1 | 3.85566 | 0.8602 | 4 | 4.0383 | 0.9844 | 4 | 0.9944 | 0.9888 | 1 | 3.8692 | 0.9619 | 4 | 12.75756 | 0.9749 | 13 | 5922 | 2801 | 2026 | 3548 | 5916 | 59.97295 | 0.9854 | 1 | 67 | 1402 | 4.778887 | 0.5316 | 0 | 251 | 1664 | 15.084135 | 0.20570 | 0 | 46 | 362 | 12.70718 | 0.05498 | 0 | 297 | 2026 | 14.659427 | 0.056430 | 0 | 844 | 3696 | 22.83550 | 0.8792 | 1 | 2528 | 5916 | 42.73158 | 0.9987 | 1 | 793 | 13.39075 | 0.4401 | 0 | 1663 | 28.08173 | 0.7575 | 1 | 573 | 4258.743 | 13.454674 | 0.42530 | 0 | 301 | 1112.258 | 27.06206 | 0.8474 | 1 | 851 | 5568 | 15.283764 | 0.9575 | 1 | 5880 | 5922.449 | 99.28326 | 0.9964 | 1 | 2801 | 22 | 0.7854338 | 0.3369 | 0 | 521 | 18.60050 | 0.8557 | 1 | 267 | 2026 | 13.178677 | 0.9482 | 1 | 297 | 2025.690 | 14.66167 | 0.9158 | 1 | 11 | 5922 | 0.1857481 | 0.5222 | 0 | 3.451330 | 0.7773 | 3 | 3.42780 | 0.9008 | 3 | 0.9964 | 0.9922 | 1 | 3.5788 | 0.9040 | 3 | 11.45433 | 0.9088 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
National
svi_national_nmtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | FIPS_st | FIPS_county | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | nmtc_eligibility | pre10_nmtc_project_cnt | pre10_nmtc_dollars | pre10_nmtc_dollars_formatted | post10_nmtc_project_cnt | post10_nmtc_dollars | post10_nmtc_dollars_formatted | nmtc_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01001020200 | 01 | 001 | 020200 | AL | Alabama | Autauga County | 3 | South Region | 6 | East South Central Division | 2020 | 816 | 730 | 495 | 1992 | 24.84940 | 0.5954 | 0 | 68 | 834 | 8.153477 | 0.57540 | 0 | 49 | 439 | 11.16173 | 0.02067 | 0 | 105 | 291 | 36.08247 | 0.30190 | 0 | 154 | 730 | 21.09589 | 0.09312 | 0 | 339 | 1265 | 26.79842 | 0.8392 | 1 | 313 | 2012 | 15.55666 | 0.6000 | 0 | 204 | 10.09901 | 0.3419 | 0 | 597 | 29.55446 | 0.8192 | 1 | 359 | 1515 | 23.69637 | 0.8791 | 1 | 132 | 456 | 28.947368 | 0.8351 | 1 | 15 | 1890 | 0.7936508 | 0.40130 | 0 | 1243 | 2020 | 61.53465 | 0.7781 | 1 | 816 | 0 | 0.0000000 | 0.1224 | 0 | 34 | 4.1666667 | 0.6664 | 0 | 13 | 730 | 1.780822 | 0.5406 | 0 | 115 | 730 | 15.753425 | 0.8382 | 1 | 0 | 2020 | 0.0000 | 0.3640 | 0 | 2.70312 | 0.5665 | 1 | 3.27660 | 0.8614 | 3 | 0.7781 | 0.7709 | 1 | 2.5316 | 0.5047 | 1 | 9.28942 | 0.6832 | 6 | 1757 | 720 | 573 | 384 | 1511 | 25.41363 | 0.6427 | 0 | 29 | 717 | 4.044630 | 0.4132 | 0 | 33 | 392 | 8.418367 | 0.03542 | 0 | 116 | 181 | 64.08840 | 0.9086 | 1 | 149 | 573 | 26.00349 | 0.40410 | 0 | 139 | 1313 | 10.58644 | 0.5601 | 0 | 91 | 1533 | 5.936073 | 0.4343 | 0 | 284 | 16.163916 | 0.5169 | 0 | 325 | 18.49744 | 0.2851 | 0 | 164 | 1208.000 | 13.57616 | 0.4127 | 0 | 42 | 359.0000 | 11.699164 | 0.3998 | 0 | 0 | 1651 | 0.0000000 | 0.09479 | 0 | 1116 | 1757.000 | 63.51736 | 0.7591 | 1 | 720 | 3 | 0.4166667 | 0.2470 | 0 | 5 | 0.6944444 | 0.5106 | 0 | 9 | 573 | 1.5706806 | 0.4688 | 0 | 57 | 573.000 | 9.947644 | 0.7317 | 0 | 212 | 1757 | 12.0660216 | 0.9549 | 1 | 2.45440 | 0.4888 | 0 | 1.70929 | 0.1025 | 0 | 0.7591 | 0.7527 | 1 | 2.9130 | 0.6862 | 1 | 7.83579 | 0.4802 | 2 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 01001020700 | 01 | 001 | 020700 | AL | Alabama | Autauga County | 3 | South Region | 6 | East South Central Division | 2664 | 1254 | 1139 | 710 | 2664 | 26.65165 | 0.6328 | 0 | 29 | 1310 | 2.213741 | 0.05255 | 0 | 134 | 710 | 18.87324 | 0.13890 | 0 | 187 | 429 | 43.58974 | 0.47090 | 0 | 321 | 1139 | 28.18262 | 0.28130 | 0 | 396 | 1852 | 21.38229 | 0.7478 | 0 | 345 | 2878 | 11.98749 | 0.4459 | 0 | 389 | 14.60210 | 0.6417 | 0 | 599 | 22.48499 | 0.4007 | 0 | 510 | 2168 | 23.52399 | 0.8752 | 1 | 228 | 712 | 32.022472 | 0.8712 | 1 | 0 | 2480 | 0.0000000 | 0.09298 | 0 | 694 | 2664 | 26.05105 | 0.5138 | 0 | 1254 | 8 | 0.6379585 | 0.2931 | 0 | 460 | 36.6826156 | 0.9714 | 1 | 0 | 1139 | 0.000000 | 0.1238 | 0 | 125 | 1139 | 10.974539 | 0.7477 | 0 | 0 | 2664 | 0.0000 | 0.3640 | 0 | 2.16035 | 0.4069 | 0 | 2.88178 | 0.6997 | 2 | 0.5138 | 0.5090 | 0 | 2.5000 | 0.4882 | 1 | 8.05593 | 0.5185 | 3 | 3562 | 1313 | 1248 | 1370 | 3528 | 38.83220 | 0.8512 | 1 | 128 | 1562 | 8.194622 | 0.7935 | 1 | 168 | 844 | 19.905213 | 0.44510 | 0 | 237 | 404 | 58.66337 | 0.8359 | 1 | 405 | 1248 | 32.45192 | 0.60420 | 0 | 396 | 2211 | 17.91045 | 0.7857 | 1 | 444 | 3547 | 12.517620 | 0.7758 | 1 | 355 | 9.966311 | 0.1800 | 0 | 954 | 26.78271 | 0.7923 | 1 | 629 | 2593.000 | 24.25762 | 0.8730 | 1 | 171 | 797.0000 | 21.455458 | 0.7186 | 0 | 0 | 3211 | 0.0000000 | 0.09479 | 0 | 1009 | 3562.000 | 28.32678 | 0.4668 | 0 | 1313 | 14 | 1.0662605 | 0.3165 | 0 | 443 | 33.7395278 | 0.9663 | 1 | 73 | 1248 | 5.8493590 | 0.8211 | 1 | 17 | 1248.000 | 1.362180 | 0.1554 | 0 | 112 | 3562 | 3.1443010 | 0.8514 | 1 | 3.81040 | 0.8569 | 4 | 2.65869 | 0.5847 | 2 | 0.4668 | 0.4629 | 0 | 3.1107 | 0.7714 | 3 | 10.04659 | 0.7851 | 9 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 01001021100 | 01 | 001 | 021100 | AL | Alabama | Autauga County | 3 | South Region | 6 | East South Central Division | 3298 | 1502 | 1323 | 860 | 3298 | 26.07641 | 0.6211 | 0 | 297 | 1605 | 18.504673 | 0.94340 | 1 | 250 | 1016 | 24.60630 | 0.32070 | 0 | 74 | 307 | 24.10423 | 0.11920 | 0 | 324 | 1323 | 24.48980 | 0.17380 | 0 | 710 | 2231 | 31.82429 | 0.8976 | 1 | 654 | 3565 | 18.34502 | 0.7018 | 0 | 411 | 12.46210 | 0.5001 | 0 | 738 | 22.37720 | 0.3934 | 0 | 936 | 2861 | 32.71583 | 0.9807 | 1 | 138 | 825 | 16.727273 | 0.5715 | 0 | 9 | 3155 | 0.2852615 | 0.25010 | 0 | 1979 | 3298 | 60.00606 | 0.7703 | 1 | 1502 | 14 | 0.9320905 | 0.3234 | 0 | 659 | 43.8748336 | 0.9849 | 1 | 44 | 1323 | 3.325775 | 0.7062 | 0 | 137 | 1323 | 10.355253 | 0.7313 | 0 | 0 | 3298 | 0.0000 | 0.3640 | 0 | 3.33770 | 0.7351 | 2 | 2.69580 | 0.6028 | 1 | 0.7703 | 0.7631 | 1 | 3.1098 | 0.7827 | 1 | 9.91360 | 0.7557 | 5 | 3499 | 1825 | 1462 | 1760 | 3499 | 50.30009 | 0.9396 | 1 | 42 | 966 | 4.347826 | 0.4539 | 0 | 426 | 1274 | 33.437991 | 0.85200 | 1 | 52 | 188 | 27.65957 | 0.1824 | 0 | 478 | 1462 | 32.69494 | 0.61110 | 0 | 422 | 2488 | 16.96141 | 0.7638 | 1 | 497 | 3499 | 14.204058 | 0.8246 | 1 | 853 | 24.378394 | 0.8688 | 1 | 808 | 23.09231 | 0.5829 | 0 | 908 | 2691.100 | 33.74084 | 0.9808 | 1 | 179 | 811.6985 | 22.052524 | 0.7323 | 0 | 8 | 3248 | 0.2463054 | 0.26220 | 0 | 1986 | 3498.713 | 56.76373 | 0.7175 | 0 | 1825 | 29 | 1.5890411 | 0.3551 | 0 | 576 | 31.5616438 | 0.9594 | 1 | 88 | 1462 | 6.0191518 | 0.8269 | 1 | 148 | 1461.993 | 10.123166 | 0.7364 | 0 | 38 | 3499 | 1.0860246 | 0.7013 | 0 | 3.59300 | 0.8073 | 3 | 3.42700 | 0.9156 | 2 | 0.7175 | 0.7114 | 0 | 3.5791 | 0.9216 | 2 | 11.31660 | 0.9150 | 7 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 01003010200 | 01 | 003 | 010200 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 2612 | 1220 | 1074 | 338 | 2605 | 12.97505 | 0.2907 | 0 | 44 | 1193 | 3.688181 | 0.14720 | 0 | 172 | 928 | 18.53448 | 0.13090 | 0 | 31 | 146 | 21.23288 | 0.09299 | 0 | 203 | 1074 | 18.90130 | 0.05657 | 0 | 455 | 1872 | 24.30556 | 0.8016 | 1 | 456 | 2730 | 16.70330 | 0.6445 | 0 | 401 | 15.35222 | 0.6847 | 0 | 563 | 21.55436 | 0.3406 | 0 | 410 | 2038 | 20.11776 | 0.7755 | 1 | 64 | 779 | 8.215661 | 0.2181 | 0 | 0 | 2510 | 0.0000000 | 0.09298 | 0 | 329 | 2612 | 12.59571 | 0.3113 | 0 | 1220 | 38 | 3.1147541 | 0.4648 | 0 | 385 | 31.5573770 | 0.9545 | 1 | 20 | 1074 | 1.862197 | 0.5509 | 0 | 43 | 1074 | 4.003724 | 0.4088 | 0 | 0 | 2612 | 0.0000 | 0.3640 | 0 | 1.94057 | 0.3398 | 1 | 2.11188 | 0.2802 | 1 | 0.3113 | 0.3084 | 0 | 2.7430 | 0.6129 | 1 | 7.10675 | 0.3771 | 3 | 2928 | 1312 | 1176 | 884 | 2928 | 30.19126 | 0.7334 | 0 | 29 | 1459 | 1.987663 | 0.1356 | 0 | 71 | 830 | 8.554217 | 0.03726 | 0 | 134 | 346 | 38.72832 | 0.3964 | 0 | 205 | 1176 | 17.43197 | 0.12010 | 0 | 294 | 2052 | 14.32749 | 0.6940 | 0 | 219 | 2925 | 7.487179 | 0.5423 | 0 | 556 | 18.989071 | 0.6705 | 0 | 699 | 23.87295 | 0.6339 | 0 | 489 | 2226.455 | 21.96317 | 0.8122 | 1 | 191 | 783.8820 | 24.365914 | 0.7799 | 1 | 0 | 2710 | 0.0000000 | 0.09479 | 0 | 398 | 2927.519 | 13.59513 | 0.2511 | 0 | 1312 | 13 | 0.9908537 | 0.3111 | 0 | 400 | 30.4878049 | 0.9557 | 1 | 6 | 1176 | 0.5102041 | 0.2590 | 0 | 81 | 1176.202 | 6.886570 | 0.6115 | 0 | 7 | 2928 | 0.2390710 | 0.4961 | 0 | 2.22540 | 0.4183 | 0 | 2.99129 | 0.7634 | 2 | 0.2511 | 0.2490 | 0 | 2.6334 | 0.5496 | 1 | 8.10119 | 0.5207 | 3 | Yes | 0 | 0 | $0 | 1 | 408000 | $408,000 | 1 |
| 01003010500 | 01 | 003 | 010500 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 4230 | 1779 | 1425 | 498 | 3443 | 14.46413 | 0.3337 | 0 | 166 | 1625 | 10.215385 | 0.71790 | 0 | 151 | 1069 | 14.12535 | 0.04638 | 0 | 196 | 356 | 55.05618 | 0.73830 | 0 | 347 | 1425 | 24.35088 | 0.17010 | 0 | 707 | 2945 | 24.00679 | 0.7967 | 1 | 528 | 4001 | 13.19670 | 0.5005 | 0 | 619 | 14.63357 | 0.6436 | 0 | 790 | 18.67612 | 0.1937 | 0 | 536 | 3096 | 17.31266 | 0.6572 | 0 | 165 | 920 | 17.934783 | 0.6102 | 0 | 20 | 4021 | 0.4973887 | 0.32320 | 0 | 754 | 4230 | 17.82506 | 0.4023 | 0 | 1779 | 97 | 5.4525014 | 0.5525 | 0 | 8 | 0.4496908 | 0.4600 | 0 | 63 | 1425 | 4.421053 | 0.7762 | 1 | 90 | 1425 | 6.315790 | 0.5691 | 0 | 787 | 4230 | 18.6052 | 0.9649 | 1 | 2.51890 | 0.5121 | 1 | 2.42790 | 0.4539 | 0 | 0.4023 | 0.3986 | 0 | 3.3227 | 0.8628 | 2 | 8.67180 | 0.6054 | 3 | 5877 | 1975 | 1836 | 820 | 5244 | 15.63692 | 0.3902 | 0 | 90 | 2583 | 3.484321 | 0.3361 | 0 | 159 | 1345 | 11.821561 | 0.10530 | 0 | 139 | 491 | 28.30957 | 0.1924 | 0 | 298 | 1836 | 16.23094 | 0.09053 | 0 | 570 | 4248 | 13.41808 | 0.6669 | 0 | 353 | 5247 | 6.727654 | 0.4924 | 0 | 1109 | 18.870172 | 0.6645 | 0 | 1144 | 19.46571 | 0.3411 | 0 | 717 | 4102.545 | 17.47696 | 0.6332 | 0 | 103 | 1286.1180 | 8.008596 | 0.2341 | 0 | 0 | 5639 | 0.0000000 | 0.09479 | 0 | 868 | 5877.481 | 14.76823 | 0.2709 | 0 | 1975 | 26 | 1.3164557 | 0.3359 | 0 | 45 | 2.2784810 | 0.6271 | 0 | 9 | 1836 | 0.4901961 | 0.2540 | 0 | 116 | 1835.798 | 6.318779 | 0.5811 | 0 | 633 | 5877 | 10.7708014 | 0.9507 | 1 | 1.97613 | 0.3410 | 0 | 1.96769 | 0.1961 | 0 | 0.2709 | 0.2686 | 0 | 2.7488 | 0.6077 | 1 | 6.96352 | 0.3406 | 1 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 |
| 01003010600 | 01 | 003 | 010600 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 3724 | 1440 | 1147 | 1973 | 3724 | 52.98067 | 0.9342 | 1 | 142 | 1439 | 9.867964 | 0.69680 | 0 | 235 | 688 | 34.15698 | 0.62950 | 0 | 187 | 459 | 40.74074 | 0.40290 | 0 | 422 | 1147 | 36.79163 | 0.55150 | 0 | 497 | 1876 | 26.49254 | 0.8354 | 1 | 511 | 3661 | 13.95794 | 0.5334 | 0 | 246 | 6.60580 | 0.1481 | 0 | 1256 | 33.72718 | 0.9305 | 1 | 496 | 2522 | 19.66693 | 0.7587 | 1 | 274 | 838 | 32.696897 | 0.8779 | 1 | 32 | 3479 | 0.9198045 | 0.42810 | 0 | 2606 | 3724 | 69.97852 | 0.8184 | 1 | 1440 | 21 | 1.4583333 | 0.3683 | 0 | 321 | 22.2916667 | 0.9036 | 1 | 97 | 1147 | 8.456844 | 0.8956 | 1 | 167 | 1147 | 14.559721 | 0.8209 | 1 | 0 | 3724 | 0.0000 | 0.3640 | 0 | 3.55130 | 0.7859 | 2 | 3.14330 | 0.8145 | 3 | 0.8184 | 0.8108 | 1 | 3.3524 | 0.8725 | 3 | 10.86540 | 0.8550 | 9 | 4115 | 1534 | 1268 | 1676 | 3997 | 41.93145 | 0.8814 | 1 | 294 | 1809 | 16.252073 | 0.9674 | 1 | 341 | 814 | 41.891892 | 0.94320 | 1 | 204 | 454 | 44.93392 | 0.5438 | 0 | 545 | 1268 | 42.98107 | 0.83620 | 1 | 624 | 2425 | 25.73196 | 0.9002 | 1 | 994 | 4115 | 24.155529 | 0.9602 | 1 | 642 | 15.601458 | 0.4841 | 0 | 1126 | 27.36331 | 0.8175 | 1 | 568 | 2989.000 | 19.00301 | 0.7045 | 0 | 212 | 715.0000 | 29.650350 | 0.8592 | 1 | 56 | 3825 | 1.4640523 | 0.53120 | 0 | 2715 | 4115.000 | 65.97813 | 0.7732 | 1 | 1534 | 0 | 0.0000000 | 0.1079 | 0 | 529 | 34.4850065 | 0.9685 | 1 | 101 | 1268 | 7.9652997 | 0.8795 | 1 | 89 | 1268.000 | 7.018927 | 0.6184 | 0 | 17 | 4115 | 0.4131227 | 0.5707 | 0 | 4.54540 | 0.9754 | 5 | 3.39650 | 0.9081 | 2 | 0.7732 | 0.7667 | 1 | 3.1450 | 0.7858 | 2 | 11.86010 | 0.9520 | 10 | Yes | 0 | 0 | $0 | 1 | 8000000 | $8,000,000 | 1 |
View LIHTC Data
Divisional
svi_divisional_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | FIPS_st | FIPS_county | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | pre10_lihtc_project_cnt | pre10_lihtc_project_dollars | post10_lihtc_project_cnt | post10_lihtc_project_dollars | lihtc_flag | lihtc_eligibility |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 04001942600 | 04 | 001 | 942600 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 1561 | 762 | 384 | 1150 | 1561 | 73.67072 | 0.9944 | 1 | 26 | 300 | 8.666667 | 0.6866 | 0 | 65 | 366 | 17.759563 | 0.10180 | 0 | 5 | 18 | 27.77778 | 0.19090 | 0 | 70 | 384 | 18.22917 | 0.05781 | 0 | 303 | 839 | 36.11442 | 0.9335 | 1 | 282 | 1578 | 17.87072 | 0.5921 | 0 | 153 | 9.801409 | 0.449600 | 0 | 560 | 35.874440 | 0.90440 | 1 | 240 | 1054 | 22.770398 | 0.90060 | 1 | 107 | 332 | 32.22892 | 0.9163 | 1 | 168 | 1431 | 11.7400419 | 0.8831 | 1 | 1561 | 1561 | 100.00000 | 0.9989 | 1 | 762 | 0 | 0.0000000 | 0.1526 | 0 | 215 | 28.21522 | 0.9088 | 1 | 117 | 384 | 30.468750 | 0.9979 | 1 | 33 | 384 | 8.593750 | 0.7842 | 1 | 0 | 1561 | 0.000000 | 0.3955 | 0 | 3.26441 | 0.7248 | 2 | 4.054000 | 0.98530 | 4 | 0.9989 | 0.9931 | 1 | 3.2390 | 0.8004 | 3 | 11.556310 | 0.8966 | 10 | 1711 | 676 | 469 | 930 | 1711 | 54.35418 | 0.9708 | 1 | 44 | 484 | 9.090909 | 0.8539 | 1 | 32 | 456 | 7.017544 | 0.02013 | 0 | 4 | 13 | 30.76923 | 0.24630 | 0 | 36 | 469 | 7.675906 | 0.005758 | 0 | 304 | 1197 | 25.396825 | 0.9056 | 1 | 686 | 1711 | 40.093513 | 0.9973 | 1 | 229 | 13.3839860 | 0.439700 | 0 | 347 | 20.280538 | 0.37880 | 0 | 245 | 1363.979 | 17.962156 | 0.6824 | 0 | 49 | 304.0000 | 16.11842 | 0.5859 | 0 | 155 | 1652 | 9.3825666 | 0.8951 | 1 | 1711 | 1710.980 | 100.00115 | 1.0000 | 1 | 676 | 0 | 0.0000000 | 0.1276 | 0 | 142 | 21.0059172 | 0.8736 | 1 | 83 | 469 | 17.697228 | 0.9774 | 1 | 99 | 469.0000 | 21.108742 | 0.9655 | 1 | 0 | 1711 | 0.0000000 | 0.2155 | 0 | 3.733358 | 0.8474 | 4 | 2.981900 | 0.73750 | 1 | 1.0000 | 0.9958 | 1 | 3.1596 | 0.7653 | 3 | 10.87486 | 0.8573 | 9 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04001942700 | 04 | 001 | 942700 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4886 | 2757 | 1291 | 2616 | 4871 | 53.70560 | 0.9480 | 1 | 163 | 1398 | 11.659514 | 0.8577 | 1 | 102 | 1113 | 9.164421 | 0.01757 | 0 | 54 | 178 | 30.33708 | 0.22790 | 0 | 156 | 1291 | 12.08366 | 0.01652 | 0 | 1039 | 2931 | 35.44865 | 0.9303 | 1 | 1873 | 5249 | 35.68299 | 0.9436 | 1 | 688 | 14.081048 | 0.687000 | 0 | 1530 | 31.313958 | 0.77180 | 1 | 772 | 3514 | 21.969266 | 0.88390 | 1 | 246 | 939 | 26.19808 | 0.8308 | 1 | 592 | 4631 | 12.7834161 | 0.8975 | 1 | 4846 | 4886 | 99.18133 | 0.9946 | 1 | 2757 | 0 | 0.0000000 | 0.1526 | 0 | 369 | 13.38411 | 0.7652 | 1 | 240 | 1291 | 18.590240 | 0.9756 | 1 | 188 | 1291 | 14.562355 | 0.9015 | 1 | 0 | 4886 | 0.000000 | 0.3955 | 0 | 3.69612 | 0.8288 | 4 | 4.071000 | 0.98700 | 4 | 0.9946 | 0.9890 | 1 | 3.1904 | 0.7848 | 3 | 11.952120 | 0.9295 | 12 | 5469 | 2222 | 1462 | 2784 | 5469 | 50.90510 | 0.9557 | 1 | 358 | 1642 | 21.802680 | 0.9925 | 1 | 114 | 1151 | 9.904431 | 0.04797 | 0 | 58 | 311 | 18.64952 | 0.09477 | 0 | 172 | 1462 | 11.764706 | 0.023990 | 0 | 852 | 3274 | 26.023213 | 0.9120 | 1 | 1856 | 5466 | 33.955360 | 0.9919 | 1 | 759 | 13.8782227 | 0.465700 | 0 | 1555 | 28.432986 | 0.77390 | 1 | 706 | 3911.002 | 18.051640 | 0.6872 | 0 | 257 | 1035.0004 | 24.83091 | 0.8039 | 1 | 396 | 5078 | 7.7983458 | 0.8624 | 1 | 5420 | 5469.002 | 99.10401 | 0.9946 | 1 | 2222 | 0 | 0.0000000 | 0.1276 | 0 | 400 | 18.0018002 | 0.8488 | 1 | 238 | 1462 | 16.279070 | 0.9710 | 1 | 175 | 1462.0007 | 11.969898 | 0.8742 | 1 | 26 | 5469 | 0.4754068 | 0.6430 | 0 | 3.876090 | 0.8796 | 4 | 3.593100 | 0.94210 | 3 | 0.9946 | 0.9905 | 1 | 3.4646 | 0.8721 | 3 | 11.92839 | 0.9425 | 11 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04001944100 | 04 | 001 | 944100 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4975 | 2485 | 1204 | 3251 | 4968 | 65.43881 | 0.9846 | 1 | 210 | 1254 | 16.746412 | 0.9576 | 1 | 122 | 905 | 13.480663 | 0.04383 | 0 | 91 | 299 | 30.43478 | 0.22960 | 0 | 213 | 1204 | 17.69103 | 0.05320 | 0 | 779 | 2325 | 33.50538 | 0.9203 | 1 | 1293 | 5511 | 23.46217 | 0.7705 | 1 | 344 | 6.914573 | 0.270100 | 0 | 1993 | 40.060302 | 0.97010 | 1 | 577 | 3087 | 18.691286 | 0.77990 | 1 | 278 | 893 | 31.13102 | 0.9038 | 1 | 308 | 4470 | 6.8903803 | 0.7895 | 1 | 4915 | 4975 | 98.79397 | 0.9929 | 1 | 2485 | 21 | 0.8450704 | 0.3700 | 0 | 428 | 17.22334 | 0.8203 | 1 | 257 | 1204 | 21.345515 | 0.9843 | 1 | 212 | 1204 | 17.607973 | 0.9391 | 1 | 0 | 4975 | 0.000000 | 0.3955 | 0 | 3.68620 | 0.8261 | 4 | 3.713400 | 0.95280 | 4 | 0.9929 | 0.9872 | 1 | 3.5092 | 0.8926 | 3 | 11.901700 | 0.9244 | 12 | 6183 | 2379 | 1424 | 3704 | 5789 | 63.98342 | 0.9912 | 1 | 425 | 1608 | 26.430348 | 0.9954 | 1 | 132 | 1163 | 11.349957 | 0.07802 | 0 | 38 | 261 | 14.55939 | 0.06498 | 0 | 170 | 1424 | 11.938202 | 0.026300 | 0 | 862 | 3259 | 26.449831 | 0.9148 | 1 | 1320 | 6183 | 21.348860 | 0.9283 | 1 | 637 | 10.3024422 | 0.271800 | 0 | 1869 | 30.228045 | 0.83960 | 1 | 626 | 3964.000 | 15.792129 | 0.5715 | 0 | 371 | 991.0000 | 37.43693 | 0.9557 | 1 | 315 | 5717 | 5.5098828 | 0.8021 | 1 | 5981 | 6182.998 | 96.73300 | 0.9841 | 1 | 2379 | 0 | 0.0000000 | 0.1276 | 0 | 442 | 18.5792350 | 0.8550 | 1 | 379 | 1424 | 26.615168 | 0.9969 | 1 | 347 | 1424.0000 | 24.367977 | 0.9758 | 1 | 394 | 6183 | 6.3723112 | 0.9380 | 1 | 3.856000 | 0.8749 | 4 | 3.440700 | 0.90700 | 3 | 0.9841 | 0.9800 | 1 | 3.8933 | 0.9609 | 4 | 12.17410 | 0.9549 | 12 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04001944300 | 04 | 001 | 944300 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 6806 | 3308 | 1826 | 4099 | 6797 | 60.30602 | 0.9762 | 1 | 403 | 1777 | 22.678672 | 0.9858 | 1 | 154 | 1457 | 10.569664 | 0.02549 | 0 | 63 | 369 | 17.07317 | 0.08684 | 0 | 217 | 1826 | 11.88390 | 0.01536 | 0 | 1432 | 3367 | 42.53044 | 0.9623 | 1 | 2305 | 7092 | 32.50141 | 0.9160 | 1 | 746 | 10.960917 | 0.517600 | 0 | 2767 | 40.655304 | 0.97610 | 1 | 842 | 4361 | 19.307498 | 0.80410 | 1 | 357 | 1163 | 30.69647 | 0.8982 | 1 | 568 | 6178 | 9.1939139 | 0.8423 | 1 | 6750 | 6806 | 99.17720 | 0.9944 | 1 | 3308 | 8 | 0.2418380 | 0.3113 | 0 | 440 | 13.30109 | 0.7638 | 1 | 404 | 1826 | 22.124863 | 0.9856 | 1 | 388 | 1826 | 21.248631 | 0.9627 | 1 | 139 | 6806 | 2.042316 | 0.8458 | 1 | 3.85566 | 0.8602 | 4 | 4.038300 | 0.98440 | 4 | 0.9944 | 0.9888 | 1 | 3.8692 | 0.9619 | 4 | 12.757560 | 0.9749 | 13 | 5922 | 2801 | 2026 | 3548 | 5916 | 59.97295 | 0.9854 | 1 | 67 | 1402 | 4.778887 | 0.5316 | 0 | 251 | 1664 | 15.084135 | 0.20570 | 0 | 46 | 362 | 12.70718 | 0.05498 | 0 | 297 | 2026 | 14.659427 | 0.056430 | 0 | 844 | 3696 | 22.835498 | 0.8792 | 1 | 2528 | 5916 | 42.731575 | 0.9987 | 1 | 793 | 13.3907464 | 0.440100 | 0 | 1663 | 28.081729 | 0.75750 | 1 | 573 | 4258.743 | 13.454674 | 0.4253 | 0 | 301 | 1112.2581 | 27.06206 | 0.8474 | 1 | 851 | 5568 | 15.2837644 | 0.9575 | 1 | 5880 | 5922.449 | 99.28326 | 0.9964 | 1 | 2801 | 22 | 0.7854338 | 0.3369 | 0 | 521 | 18.6004998 | 0.8557 | 1 | 267 | 2026 | 13.178677 | 0.9482 | 1 | 297 | 2025.6898 | 14.661672 | 0.9158 | 1 | 11 | 5922 | 0.1857481 | 0.5222 | 0 | 3.451330 | 0.7773 | 3 | 3.427800 | 0.90080 | 3 | 0.9964 | 0.9922 | 1 | 3.5788 | 0.9040 | 3 | 11.45433 | 0.9088 | 10 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04005000800 | 04 | 005 | 000800 | AZ | Arizona | Coconino County | 4 | West Region | 8 | Mountain Division | 3912 | 1200 | 1057 | 1511 | 2859 | 52.85065 | 0.9430 | 1 | 54 | 1952 | 2.766393 | 0.1150 | 0 | 71 | 192 | 36.979167 | 0.73370 | 0 | 509 | 865 | 58.84393 | 0.83080 | 1 | 580 | 1057 | 54.87228 | 0.96160 | 1 | 265 | 1897 | 13.96943 | 0.6489 | 0 | 995 | 3589 | 27.72360 | 0.8536 | 1 | 121 | 3.093047 | 0.062070 | 0 | 208 | 5.316973 | 0.02835 | 0 | 248 | 3170 | 7.823344 | 0.15510 | 0 | 53 | 311 | 17.04180 | 0.5919 | 0 | 26 | 3898 | 0.6670087 | 0.3063 | 0 | 1410 | 3912 | 36.04294 | 0.6285 | 0 | 1200 | 155 | 12.9166667 | 0.7329 | 0 | 3 | 0.25000 | 0.3706 | 0 | 31 | 1057 | 2.932829 | 0.6261 | 0 | 33 | 1057 | 3.122044 | 0.4682 | 0 | 1043 | 3912 | 26.661554 | 0.9826 | 1 | 3.52210 | 0.7887 | 3 | 1.143720 | 0.02019 | 0 | 0.6285 | 0.6250 | 0 | 3.1804 | 0.7810 | 1 | 8.474720 | 0.5850 | 4 | 6428 | 2343 | 2163 | 3238 | 5850 | 55.35043 | 0.9741 | 1 | 399 | 3753 | 10.631495 | 0.9047 | 1 | 43 | 312 | 13.782051 | 0.15050 | 0 | 1188 | 1850 | 64.21622 | 0.93540 | 1 | 1231 | 2162 | 56.938020 | 0.988900 | 1 | 364 | 2823 | 12.894084 | 0.7116 | 0 | 478 | 5900 | 8.101695 | 0.4937 | 0 | 262 | 4.0759179 | 0.030250 | 0 | 634 | 9.863099 | 0.06202 | 0 | 497 | 5227.333 | 9.507716 | 0.1782 | 0 | 112 | 544.6422 | 20.56396 | 0.7139 | 0 | 56 | 6207 | 0.9022072 | 0.4074 | 0 | 2862 | 6428.175 | 44.52274 | 0.6490 | 0 | 2343 | 838 | 35.7661118 | 0.9165 | 1 | 11 | 0.4694836 | 0.4053 | 0 | 116 | 2163 | 5.362922 | 0.7808 | 1 | 166 | 2162.6681 | 7.675704 | 0.7658 | 1 | 759 | 6428 | 11.8077162 | 0.9625 | 1 | 4.073000 | 0.9190 | 3 | 1.391770 | 0.04857 | 0 | 0.6490 | 0.6463 | 0 | 3.8309 | 0.9524 | 4 | 9.94467 | 0.7611 | 7 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04005001000 | 04 | 005 | 001000 | AZ | Arizona | Coconino County | 4 | West Region | 8 | Mountain Division | 7519 | 863 | 763 | 1197 | 1744 | 68.63532 | 0.9894 | 1 | 1067 | 4202 | 25.392670 | 0.9925 | 1 | 17 | 25 | 68.000000 | 0.99610 | 1 | 484 | 738 | 65.58266 | 0.91810 | 1 | 501 | 763 | 65.66186 | 0.99650 | 1 | 47 | 886 | 5.30474 | 0.2676 | 0 | 1429 | 8331 | 17.15280 | 0.5641 | 0 | 0 | 0.000000 | 0.003736 | 0 | 310 | 4.122889 | 0.02165 | 0 | 54 | 1560 | 3.461539 | 0.01727 | 0 | 23 | 174 | 13.21839 | 0.4495 | 0 | 233 | 7411 | 3.1439752 | 0.6314 | 0 | 2495 | 7519 | 33.18260 | 0.5941 | 0 | 863 | 441 | 51.1008111 | 0.9666 | 1 | 35 | 4.05562 | 0.6079 | 0 | 14 | 763 | 1.834862 | 0.4856 | 0 | 119 | 763 | 15.596330 | 0.9127 | 1 | 5775 | 7519 | 76.805426 | 0.9946 | 1 | 3.81010 | 0.8520 | 3 | 1.123556 | 0.01848 | 0 | 0.5941 | 0.5907 | 0 | 3.9674 | 0.9733 | 3 | 9.495156 | 0.7036 | 6 | 13499 | 815 | 675 | 1056 | 1313 | 80.42650 | 0.9987 | 1 | 1353 | 6344 | 21.327238 | 0.9918 | 1 | 22 | 35 | 62.857143 | 0.99810 | 1 | 500 | 641 | 78.00312 | 0.99310 | 1 | 522 | 676 | 77.218935 | 0.999600 | 1 | 29 | 460 | 6.304348 | 0.4346 | 0 | 1051 | 13483 | 7.795001 | 0.4716 | 0 | 17 | 0.1259353 | 0.004211 | 0 | 221 | 1.637158 | 0.01474 | 0 | 125 | 1282.667 | 9.745322 | 0.1874 | 0 | 42 | 114.3578 | 36.72685 | 0.9505 | 1 | 207 | 13491 | 1.5343562 | 0.5203 | 0 | 4803 | 13498.825 | 35.58088 | 0.5539 | 0 | 815 | 550 | 67.4846626 | 0.9864 | 1 | 7 | 0.8588957 | 0.4653 | 0 | 62 | 675 | 9.185185 | 0.8933 | 1 | 134 | 675.3319 | 19.842095 | 0.9607 | 1 | 12185 | 13499 | 90.2659456 | 0.9960 | 1 | 3.896300 | 0.8850 | 3 | 1.677151 | 0.11070 | 1 | 0.5539 | 0.5516 | 0 | 4.3017 | 0.9882 | 4 | 10.42905 | 0.8107 | 8 | 0 | 0 | 0 | 0 | 0 | Yes |
National
svi_divisional_lihtc %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | FIPS_st | FIPS_county | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | pre10_lihtc_project_cnt | pre10_lihtc_project_dollars | post10_lihtc_project_cnt | post10_lihtc_project_dollars | lihtc_flag | lihtc_eligibility |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 04001942600 | 04 | 001 | 942600 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 1561 | 762 | 384 | 1150 | 1561 | 73.67072 | 0.9944 | 1 | 26 | 300 | 8.666667 | 0.6866 | 0 | 65 | 366 | 17.759563 | 0.10180 | 0 | 5 | 18 | 27.77778 | 0.19090 | 0 | 70 | 384 | 18.22917 | 0.05781 | 0 | 303 | 839 | 36.11442 | 0.9335 | 1 | 282 | 1578 | 17.87072 | 0.5921 | 0 | 153 | 9.801409 | 0.449600 | 0 | 560 | 35.874440 | 0.90440 | 1 | 240 | 1054 | 22.770398 | 0.90060 | 1 | 107 | 332 | 32.22892 | 0.9163 | 1 | 168 | 1431 | 11.7400419 | 0.8831 | 1 | 1561 | 1561 | 100.00000 | 0.9989 | 1 | 762 | 0 | 0.0000000 | 0.1526 | 0 | 215 | 28.21522 | 0.9088 | 1 | 117 | 384 | 30.468750 | 0.9979 | 1 | 33 | 384 | 8.593750 | 0.7842 | 1 | 0 | 1561 | 0.000000 | 0.3955 | 0 | 3.26441 | 0.7248 | 2 | 4.054000 | 0.98530 | 4 | 0.9989 | 0.9931 | 1 | 3.2390 | 0.8004 | 3 | 11.556310 | 0.8966 | 10 | 1711 | 676 | 469 | 930 | 1711 | 54.35418 | 0.9708 | 1 | 44 | 484 | 9.090909 | 0.8539 | 1 | 32 | 456 | 7.017544 | 0.02013 | 0 | 4 | 13 | 30.76923 | 0.24630 | 0 | 36 | 469 | 7.675906 | 0.005758 | 0 | 304 | 1197 | 25.396825 | 0.9056 | 1 | 686 | 1711 | 40.093513 | 0.9973 | 1 | 229 | 13.3839860 | 0.439700 | 0 | 347 | 20.280538 | 0.37880 | 0 | 245 | 1363.979 | 17.962156 | 0.6824 | 0 | 49 | 304.0000 | 16.11842 | 0.5859 | 0 | 155 | 1652 | 9.3825666 | 0.8951 | 1 | 1711 | 1710.980 | 100.00115 | 1.0000 | 1 | 676 | 0 | 0.0000000 | 0.1276 | 0 | 142 | 21.0059172 | 0.8736 | 1 | 83 | 469 | 17.697228 | 0.9774 | 1 | 99 | 469.0000 | 21.108742 | 0.9655 | 1 | 0 | 1711 | 0.0000000 | 0.2155 | 0 | 3.733358 | 0.8474 | 4 | 2.981900 | 0.73750 | 1 | 1.0000 | 0.9958 | 1 | 3.1596 | 0.7653 | 3 | 10.87486 | 0.8573 | 9 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04001942700 | 04 | 001 | 942700 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4886 | 2757 | 1291 | 2616 | 4871 | 53.70560 | 0.9480 | 1 | 163 | 1398 | 11.659514 | 0.8577 | 1 | 102 | 1113 | 9.164421 | 0.01757 | 0 | 54 | 178 | 30.33708 | 0.22790 | 0 | 156 | 1291 | 12.08366 | 0.01652 | 0 | 1039 | 2931 | 35.44865 | 0.9303 | 1 | 1873 | 5249 | 35.68299 | 0.9436 | 1 | 688 | 14.081048 | 0.687000 | 0 | 1530 | 31.313958 | 0.77180 | 1 | 772 | 3514 | 21.969266 | 0.88390 | 1 | 246 | 939 | 26.19808 | 0.8308 | 1 | 592 | 4631 | 12.7834161 | 0.8975 | 1 | 4846 | 4886 | 99.18133 | 0.9946 | 1 | 2757 | 0 | 0.0000000 | 0.1526 | 0 | 369 | 13.38411 | 0.7652 | 1 | 240 | 1291 | 18.590240 | 0.9756 | 1 | 188 | 1291 | 14.562355 | 0.9015 | 1 | 0 | 4886 | 0.000000 | 0.3955 | 0 | 3.69612 | 0.8288 | 4 | 4.071000 | 0.98700 | 4 | 0.9946 | 0.9890 | 1 | 3.1904 | 0.7848 | 3 | 11.952120 | 0.9295 | 12 | 5469 | 2222 | 1462 | 2784 | 5469 | 50.90510 | 0.9557 | 1 | 358 | 1642 | 21.802680 | 0.9925 | 1 | 114 | 1151 | 9.904431 | 0.04797 | 0 | 58 | 311 | 18.64952 | 0.09477 | 0 | 172 | 1462 | 11.764706 | 0.023990 | 0 | 852 | 3274 | 26.023213 | 0.9120 | 1 | 1856 | 5466 | 33.955360 | 0.9919 | 1 | 759 | 13.8782227 | 0.465700 | 0 | 1555 | 28.432986 | 0.77390 | 1 | 706 | 3911.002 | 18.051640 | 0.6872 | 0 | 257 | 1035.0004 | 24.83091 | 0.8039 | 1 | 396 | 5078 | 7.7983458 | 0.8624 | 1 | 5420 | 5469.002 | 99.10401 | 0.9946 | 1 | 2222 | 0 | 0.0000000 | 0.1276 | 0 | 400 | 18.0018002 | 0.8488 | 1 | 238 | 1462 | 16.279070 | 0.9710 | 1 | 175 | 1462.0007 | 11.969898 | 0.8742 | 1 | 26 | 5469 | 0.4754068 | 0.6430 | 0 | 3.876090 | 0.8796 | 4 | 3.593100 | 0.94210 | 3 | 0.9946 | 0.9905 | 1 | 3.4646 | 0.8721 | 3 | 11.92839 | 0.9425 | 11 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04001944100 | 04 | 001 | 944100 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4975 | 2485 | 1204 | 3251 | 4968 | 65.43881 | 0.9846 | 1 | 210 | 1254 | 16.746412 | 0.9576 | 1 | 122 | 905 | 13.480663 | 0.04383 | 0 | 91 | 299 | 30.43478 | 0.22960 | 0 | 213 | 1204 | 17.69103 | 0.05320 | 0 | 779 | 2325 | 33.50538 | 0.9203 | 1 | 1293 | 5511 | 23.46217 | 0.7705 | 1 | 344 | 6.914573 | 0.270100 | 0 | 1993 | 40.060302 | 0.97010 | 1 | 577 | 3087 | 18.691286 | 0.77990 | 1 | 278 | 893 | 31.13102 | 0.9038 | 1 | 308 | 4470 | 6.8903803 | 0.7895 | 1 | 4915 | 4975 | 98.79397 | 0.9929 | 1 | 2485 | 21 | 0.8450704 | 0.3700 | 0 | 428 | 17.22334 | 0.8203 | 1 | 257 | 1204 | 21.345515 | 0.9843 | 1 | 212 | 1204 | 17.607973 | 0.9391 | 1 | 0 | 4975 | 0.000000 | 0.3955 | 0 | 3.68620 | 0.8261 | 4 | 3.713400 | 0.95280 | 4 | 0.9929 | 0.9872 | 1 | 3.5092 | 0.8926 | 3 | 11.901700 | 0.9244 | 12 | 6183 | 2379 | 1424 | 3704 | 5789 | 63.98342 | 0.9912 | 1 | 425 | 1608 | 26.430348 | 0.9954 | 1 | 132 | 1163 | 11.349957 | 0.07802 | 0 | 38 | 261 | 14.55939 | 0.06498 | 0 | 170 | 1424 | 11.938202 | 0.026300 | 0 | 862 | 3259 | 26.449831 | 0.9148 | 1 | 1320 | 6183 | 21.348860 | 0.9283 | 1 | 637 | 10.3024422 | 0.271800 | 0 | 1869 | 30.228045 | 0.83960 | 1 | 626 | 3964.000 | 15.792129 | 0.5715 | 0 | 371 | 991.0000 | 37.43693 | 0.9557 | 1 | 315 | 5717 | 5.5098828 | 0.8021 | 1 | 5981 | 6182.998 | 96.73300 | 0.9841 | 1 | 2379 | 0 | 0.0000000 | 0.1276 | 0 | 442 | 18.5792350 | 0.8550 | 1 | 379 | 1424 | 26.615168 | 0.9969 | 1 | 347 | 1424.0000 | 24.367977 | 0.9758 | 1 | 394 | 6183 | 6.3723112 | 0.9380 | 1 | 3.856000 | 0.8749 | 4 | 3.440700 | 0.90700 | 3 | 0.9841 | 0.9800 | 1 | 3.8933 | 0.9609 | 4 | 12.17410 | 0.9549 | 12 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04001944300 | 04 | 001 | 944300 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 6806 | 3308 | 1826 | 4099 | 6797 | 60.30602 | 0.9762 | 1 | 403 | 1777 | 22.678672 | 0.9858 | 1 | 154 | 1457 | 10.569664 | 0.02549 | 0 | 63 | 369 | 17.07317 | 0.08684 | 0 | 217 | 1826 | 11.88390 | 0.01536 | 0 | 1432 | 3367 | 42.53044 | 0.9623 | 1 | 2305 | 7092 | 32.50141 | 0.9160 | 1 | 746 | 10.960917 | 0.517600 | 0 | 2767 | 40.655304 | 0.97610 | 1 | 842 | 4361 | 19.307498 | 0.80410 | 1 | 357 | 1163 | 30.69647 | 0.8982 | 1 | 568 | 6178 | 9.1939139 | 0.8423 | 1 | 6750 | 6806 | 99.17720 | 0.9944 | 1 | 3308 | 8 | 0.2418380 | 0.3113 | 0 | 440 | 13.30109 | 0.7638 | 1 | 404 | 1826 | 22.124863 | 0.9856 | 1 | 388 | 1826 | 21.248631 | 0.9627 | 1 | 139 | 6806 | 2.042316 | 0.8458 | 1 | 3.85566 | 0.8602 | 4 | 4.038300 | 0.98440 | 4 | 0.9944 | 0.9888 | 1 | 3.8692 | 0.9619 | 4 | 12.757560 | 0.9749 | 13 | 5922 | 2801 | 2026 | 3548 | 5916 | 59.97295 | 0.9854 | 1 | 67 | 1402 | 4.778887 | 0.5316 | 0 | 251 | 1664 | 15.084135 | 0.20570 | 0 | 46 | 362 | 12.70718 | 0.05498 | 0 | 297 | 2026 | 14.659427 | 0.056430 | 0 | 844 | 3696 | 22.835498 | 0.8792 | 1 | 2528 | 5916 | 42.731575 | 0.9987 | 1 | 793 | 13.3907464 | 0.440100 | 0 | 1663 | 28.081729 | 0.75750 | 1 | 573 | 4258.743 | 13.454674 | 0.4253 | 0 | 301 | 1112.2581 | 27.06206 | 0.8474 | 1 | 851 | 5568 | 15.2837644 | 0.9575 | 1 | 5880 | 5922.449 | 99.28326 | 0.9964 | 1 | 2801 | 22 | 0.7854338 | 0.3369 | 0 | 521 | 18.6004998 | 0.8557 | 1 | 267 | 2026 | 13.178677 | 0.9482 | 1 | 297 | 2025.6898 | 14.661672 | 0.9158 | 1 | 11 | 5922 | 0.1857481 | 0.5222 | 0 | 3.451330 | 0.7773 | 3 | 3.427800 | 0.90080 | 3 | 0.9964 | 0.9922 | 1 | 3.5788 | 0.9040 | 3 | 11.45433 | 0.9088 | 10 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04005000800 | 04 | 005 | 000800 | AZ | Arizona | Coconino County | 4 | West Region | 8 | Mountain Division | 3912 | 1200 | 1057 | 1511 | 2859 | 52.85065 | 0.9430 | 1 | 54 | 1952 | 2.766393 | 0.1150 | 0 | 71 | 192 | 36.979167 | 0.73370 | 0 | 509 | 865 | 58.84393 | 0.83080 | 1 | 580 | 1057 | 54.87228 | 0.96160 | 1 | 265 | 1897 | 13.96943 | 0.6489 | 0 | 995 | 3589 | 27.72360 | 0.8536 | 1 | 121 | 3.093047 | 0.062070 | 0 | 208 | 5.316973 | 0.02835 | 0 | 248 | 3170 | 7.823344 | 0.15510 | 0 | 53 | 311 | 17.04180 | 0.5919 | 0 | 26 | 3898 | 0.6670087 | 0.3063 | 0 | 1410 | 3912 | 36.04294 | 0.6285 | 0 | 1200 | 155 | 12.9166667 | 0.7329 | 0 | 3 | 0.25000 | 0.3706 | 0 | 31 | 1057 | 2.932829 | 0.6261 | 0 | 33 | 1057 | 3.122044 | 0.4682 | 0 | 1043 | 3912 | 26.661554 | 0.9826 | 1 | 3.52210 | 0.7887 | 3 | 1.143720 | 0.02019 | 0 | 0.6285 | 0.6250 | 0 | 3.1804 | 0.7810 | 1 | 8.474720 | 0.5850 | 4 | 6428 | 2343 | 2163 | 3238 | 5850 | 55.35043 | 0.9741 | 1 | 399 | 3753 | 10.631495 | 0.9047 | 1 | 43 | 312 | 13.782051 | 0.15050 | 0 | 1188 | 1850 | 64.21622 | 0.93540 | 1 | 1231 | 2162 | 56.938020 | 0.988900 | 1 | 364 | 2823 | 12.894084 | 0.7116 | 0 | 478 | 5900 | 8.101695 | 0.4937 | 0 | 262 | 4.0759179 | 0.030250 | 0 | 634 | 9.863099 | 0.06202 | 0 | 497 | 5227.333 | 9.507716 | 0.1782 | 0 | 112 | 544.6422 | 20.56396 | 0.7139 | 0 | 56 | 6207 | 0.9022072 | 0.4074 | 0 | 2862 | 6428.175 | 44.52274 | 0.6490 | 0 | 2343 | 838 | 35.7661118 | 0.9165 | 1 | 11 | 0.4694836 | 0.4053 | 0 | 116 | 2163 | 5.362922 | 0.7808 | 1 | 166 | 2162.6681 | 7.675704 | 0.7658 | 1 | 759 | 6428 | 11.8077162 | 0.9625 | 1 | 4.073000 | 0.9190 | 3 | 1.391770 | 0.04857 | 0 | 0.6490 | 0.6463 | 0 | 3.8309 | 0.9524 | 4 | 9.94467 | 0.7611 | 7 | 0 | 0 | 0 | 0 | 0 | Yes |
| 04005001000 | 04 | 005 | 001000 | AZ | Arizona | Coconino County | 4 | West Region | 8 | Mountain Division | 7519 | 863 | 763 | 1197 | 1744 | 68.63532 | 0.9894 | 1 | 1067 | 4202 | 25.392670 | 0.9925 | 1 | 17 | 25 | 68.000000 | 0.99610 | 1 | 484 | 738 | 65.58266 | 0.91810 | 1 | 501 | 763 | 65.66186 | 0.99650 | 1 | 47 | 886 | 5.30474 | 0.2676 | 0 | 1429 | 8331 | 17.15280 | 0.5641 | 0 | 0 | 0.000000 | 0.003736 | 0 | 310 | 4.122889 | 0.02165 | 0 | 54 | 1560 | 3.461539 | 0.01727 | 0 | 23 | 174 | 13.21839 | 0.4495 | 0 | 233 | 7411 | 3.1439752 | 0.6314 | 0 | 2495 | 7519 | 33.18260 | 0.5941 | 0 | 863 | 441 | 51.1008111 | 0.9666 | 1 | 35 | 4.05562 | 0.6079 | 0 | 14 | 763 | 1.834862 | 0.4856 | 0 | 119 | 763 | 15.596330 | 0.9127 | 1 | 5775 | 7519 | 76.805426 | 0.9946 | 1 | 3.81010 | 0.8520 | 3 | 1.123556 | 0.01848 | 0 | 0.5941 | 0.5907 | 0 | 3.9674 | 0.9733 | 3 | 9.495156 | 0.7036 | 6 | 13499 | 815 | 675 | 1056 | 1313 | 80.42650 | 0.9987 | 1 | 1353 | 6344 | 21.327238 | 0.9918 | 1 | 22 | 35 | 62.857143 | 0.99810 | 1 | 500 | 641 | 78.00312 | 0.99310 | 1 | 522 | 676 | 77.218935 | 0.999600 | 1 | 29 | 460 | 6.304348 | 0.4346 | 0 | 1051 | 13483 | 7.795001 | 0.4716 | 0 | 17 | 0.1259353 | 0.004211 | 0 | 221 | 1.637158 | 0.01474 | 0 | 125 | 1282.667 | 9.745322 | 0.1874 | 0 | 42 | 114.3578 | 36.72685 | 0.9505 | 1 | 207 | 13491 | 1.5343562 | 0.5203 | 0 | 4803 | 13498.825 | 35.58088 | 0.5539 | 0 | 815 | 550 | 67.4846626 | 0.9864 | 1 | 7 | 0.8588957 | 0.4653 | 0 | 62 | 675 | 9.185185 | 0.8933 | 1 | 134 | 675.3319 | 19.842095 | 0.9607 | 1 | 12185 | 13499 | 90.2659456 | 0.9960 | 1 | 3.896300 | 0.8850 | 3 | 1.677151 | 0.11070 | 1 | 0.5539 | 0.5516 | 0 | 4.3017 | 0.9882 | 4 | 10.42905 | 0.8107 | 8 | 0 | 0 | 0 | 0 | 0 | Yes |
Housing Price Index Data
hpi_df <- read.csv("https://r-class.github.io/paf-515-course-materials/data/raw/HPI/HPI_AT_BDL_tract.csv")
hpi_df_10_20 <- hpi_df %>%
mutate(GEOID10 = str_pad(tract, 11, "left", pad=0)) %>%
filter(year %in% c(2010, 2020)) %>%
select(GEOID10, state_abbr, year, hpi) %>%
pivot_wider(names_from = year, values_from = hpi) %>%
mutate(housing_price_index10 = `2010`,
housing_price_index20 = `2020`) %>%
select(GEOID10, state_abbr, housing_price_index10, housing_price_index20)
# View data
hpi_df_10_20 %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID10 | state_abbr | housing_price_index10 | housing_price_index20 |
|---|---|---|---|
| 01001020100 | AL | 132.35 | 152.78 |
| 01001020200 | AL | 123.78 | 123.37 |
| 01001020300 | AL | 158.57 | 167.01 |
| 01001020400 | AL | 165.11 | 179.60 |
| 01001020501 | AL | 172.55 | 180.96 |
| 01001020502 | AL | 158.75 | 164.25 |
# Drop state_abbr column for joining
hpi_df_10_20 <- hpi_df_10_20 %>% select(-state_abbr)
Core Based statistical Areas (CBSA) Crosswalk
msa_csa_crosswalk <- rio::import("https://r-class.github.io/paf-515-course-materials/data/raw/CSA_MSA_Crosswalk/qcew-county-msa-csa-crosswalk.xlsx", which=4)
msa_csa_crosswalk <- msa_csa_crosswalk %>%
mutate(county_fips = str_pad(`County Code`, 5, "left", pad=0),
cbsa = coalesce(`CSA Title`, `MSA Title`),
cbsa_code = coalesce(`CSA Code`, `MSA Code`),
county_title = `County Title`) %>%
select(county_fips, county_title, cbsa, cbsa_code)
msa_csa_crosswalk %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| county_fips | county_title | cbsa | cbsa_code |
|---|---|---|---|
| 01001 | Autauga County, Alabama | Montgomery-Alexander City, AL CSA | CS388 |
| 01003 | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01005 | Barbour County, Alabama | Eufaula, AL-GA MicroSA | C2164 |
| 01007 | Bibb County, Alabama | Birmingham-Hoover-Cullman, AL CSA | CS142 |
| 01009 | Blount County, Alabama | Birmingham-Hoover-Cullman, AL CSA | CS142 |
| 01015 | Calhoun County, Alabama | Anniston-Oxford, AL MSA | C1150 |
Census Data
states <- list(svi_national_nmtc$state %>% unique())
states
## [[1]]
## [1] "AL" "AK" "AZ" "AR" "CA" "CO" "CT" "DE" "DC" "FL" "GA" "HI" "ID" "IL" "IN"
## [16] "IA" "KS" "KY" "LA" "ME" "MD" "MA" "MI" "MN" "MS" "MO" "MT" "NE" "NV" "NH"
## [31] "NJ" "NM" "NY" "NC" "ND" "OH" "OK" "OR" "PA" "RI" "SC" "SD" "TN" "TX" "UT"
## [46] "VT" "VA" "WA" "WV" "WI" "WY"
census_pull10 <- lapply(states, census_pull, yr = 2010)
census_pull10_df <- census_pull10[[1]] %>%
# Drop margin of error column
select(-moe) %>%
# Add suffix to variable names
mutate(variable = paste0(variable, "_10")) %>%
# Pivot data frame
pivot_wider(
names_from = variable,
values_from = c(estimate)
)
census_pull10_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID | NAME | Median_Income_10 | Median_Home_Value_10 |
|---|---|---|---|
| 01001020100 | Census Tract 201, Autauga County, Alabama | 31769 | 120700 |
| 01001020200 | Census Tract 202, Autauga County, Alabama | 19437 | 138500 |
| 01001020300 | Census Tract 203, Autauga County, Alabama | 24146 | 111300 |
| 01001020400 | Census Tract 204, Autauga County, Alabama | 27735 | 126300 |
| 01001020500 | Census Tract 205, Autauga County, Alabama | 35517 | 173000 |
| 01001020600 | Census Tract 206, Autauga County, Alabama | 24597 | 110700 |
| 01001020700 | Census Tract 207, Autauga County, Alabama | 22114 | 93800 |
| 01001020801 | Census Tract 208.01, Autauga County, Alabama | 30841 | 258000 |
| 01001020802 | Census Tract 208.02, Autauga County, Alabama | 29006 | 145100 |
| 01001020900 | Census Tract 209, Autauga County, Alabama | 24841 | 108000 |
census_pull19 <- lapply(states, census_pull, yr = 2019)
census_pull19_df <- census_pull19[[1]] %>%
# Select columns
select(GEOID, NAME, variable, estimate, moe) %>%
# Create individual FIPS columns for state, county, and tract
mutate(FIPS_st = substr(GEOID, 1, 2),
FIPS_county = substr(GEOID, 3, 5),
FIPS_tract = substr(GEOID, 6, 11)) %>%
# Los Angeles, CA Census Tract fixes
mutate(FIPS_tract2 = if_else((FIPS_county == "037" & FIPS_st == "06" & FIPS_tract == "137000"), "930401", FIPS_tract )) %>%
# Pima County, AZ Census Tract fixes
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "002704"), "002701", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "002906"), "002903", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "004118"), "410501", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "004121"), "410502", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "004125"), "410503", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "005200"), "470400", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "019" & FIPS_st == "04" & FIPS_tract == "005300"), "470500", FIPS_tract2 )) %>%
# Madison County, NY Census Tract fixes
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030101"), "940101", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030102"), "940102", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030103"), "940103", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030200"), "940200", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030300"), "940300", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030401"), "940401", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030403"), "940403", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030600"), "940600", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "053" & FIPS_st == "36" & FIPS_tract == "030402"), "940700", FIPS_tract2 )) %>%
# Oneida County, NY Census Tract fixes
mutate(FIPS_tract2 = if_else((FIPS_county == "065" & FIPS_st == "36" & FIPS_tract == "024800"), "940000", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "065" & FIPS_st == "36" & FIPS_tract == "024700"), "940100", FIPS_tract2 )) %>%
mutate(FIPS_tract2 = if_else((FIPS_county == "065" & FIPS_st == "36" & FIPS_tract == "024900"), "940200", FIPS_tract2 )) %>%
# Move columns in data set
relocate(c(FIPS_st, FIPS_county, FIPS_tract, FIPS_tract2),.after = GEOID) %>%
# Create new GEOID column
mutate(GEOID = paste0(FIPS_st, FIPS_county, FIPS_tract2)) %>%
# Drop newly created FIPS columns and margin of error
select(-FIPS_st, -FIPS_county, -FIPS_tract, -FIPS_tract2, -moe) %>%
# Add suffix
mutate(variable = paste0(variable, "_19")) %>%
# Pivot data set
pivot_wider(
names_from = variable,
values_from = c(estimate)
)
census_pull19_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID | NAME | Median_Income_19 | Median_Home_Value_19 |
|---|---|---|---|
| 01001020100 | Census Tract 201, Autauga County, Alabama | 25970 | 136100 |
| 01001020200 | Census Tract 202, Autauga County, Alabama | 20154 | 90500 |
| 01001020300 | Census Tract 203, Autauga County, Alabama | 27383 | 122600 |
| 01001020400 | Census Tract 204, Autauga County, Alabama | 34620 | 152700 |
| 01001020500 | Census Tract 205, Autauga County, Alabama | 41178 | 186900 |
| 01001020600 | Census Tract 206, Autauga County, Alabama | 21146 | 103600 |
| 01001020700 | Census Tract 207, Autauga County, Alabama | 20934 | 82400 |
| 01001020801 | Census Tract 208.01, Autauga County, Alabama | 31667 | 322900 |
| 01001020802 | Census Tract 208.02, Autauga County, Alabama | 33086 | 171500 |
| 01001020900 | Census Tract 209, Autauga County, Alabama | 32677 | 156900 |
inflation_adj = 1.16
# Join 2010 and 2019 Median Income and Home Value Data
census_pull_df <- left_join(census_pull10_df, census_pull19_df[c("GEOID", "Median_Income_19", "Median_Home_Value_19")], join_by("GEOID" == "GEOID"))
# Create new inflation adjusted columns for 2010 median income and median home value, find changes over time
census_pull_df <- census_pull_df %>%
mutate(Median_Income_10adj = Median_Income_10*inflation_adj,
Median_Home_Value_10adj = Median_Home_Value_10*inflation_adj,
Median_Income_Change = Median_Income_19 - Median_Income_10adj,
Median_Income_Change_pct = (Median_Income_19 - Median_Income_10adj)/Median_Income_10adj,
Median_Home_Value_Change = Median_Home_Value_19 - Median_Home_Value_10adj,
Median_Home_Value_Change_pct = (Median_Home_Value_19 - Median_Home_Value_10adj)/Median_Home_Value_10adj)
# View data
census_pull_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID | NAME | Median_Income_10 | Median_Home_Value_10 | Median_Income_19 | Median_Home_Value_19 | Median_Income_10adj | Median_Home_Value_10adj | Median_Income_Change | Median_Income_Change_pct | Median_Home_Value_Change | Median_Home_Value_Change_pct |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 01001020100 | Census Tract 201, Autauga County, Alabama | 31769 | 120700 | 25970 | 136100 | 36852.04 | 140012 | -10882.04 | -0.2952900 | -3912 | -0.0279405 |
| 01001020200 | Census Tract 202, Autauga County, Alabama | 19437 | 138500 | 20154 | 90500 | 22546.92 | 160660 | -2392.92 | -0.1061307 | -70160 | -0.4366986 |
| 01001020300 | Census Tract 203, Autauga County, Alabama | 24146 | 111300 | 27383 | 122600 | 28009.36 | 129108 | -626.36 | -0.0223625 | -6508 | -0.0504074 |
| 01001020400 | Census Tract 204, Autauga County, Alabama | 27735 | 126300 | 34620 | 152700 | 32172.60 | 146508 | 2447.40 | 0.0760709 | 6192 | 0.0422639 |
| 01001020500 | Census Tract 205, Autauga County, Alabama | 35517 | 173000 | 41178 | 186900 | 41199.72 | 200680 | -21.72 | -0.0005272 | -13780 | -0.0686665 |
| 01001020600 | Census Tract 206, Autauga County, Alabama | 24597 | 110700 | 21146 | 103600 | 28532.52 | 128412 | -7386.52 | -0.2588807 | -24812 | -0.1932218 |
| 01001020700 | Census Tract 207, Autauga County, Alabama | 22114 | 93800 | 20934 | 82400 | 25652.24 | 108808 | -4718.24 | -0.1839309 | -26408 | -0.2427027 |
| 01001020801 | Census Tract 208.01, Autauga County, Alabama | 30841 | 258000 | 31667 | 322900 | 35775.56 | 299280 | -4108.56 | -0.1148426 | 23620 | 0.0789227 |
| 01001020802 | Census Tract 208.02, Autauga County, Alabama | 29006 | 145100 | 33086 | 171500 | 33646.96 | 168316 | -560.96 | -0.0166719 | 3184 | 0.0189168 |
| 01001020900 | Census Tract 209, Autauga County, Alabama | 24841 | 108000 | 32677 | 156900 | 28815.56 | 125280 | 3861.44 | 0.1340054 | 31620 | 0.2523946 |
NMTC Data Sets
Divisional
svi_divisional_nmtc_df0 <- left_join(svi_divisional_nmtc, census_pull_df, join_by("GEOID_2010_trt" == "GEOID"))
svi_divisional_nmtc_df1 <- left_join(svi_divisional_nmtc_df0, hpi_df_10_20, join_by("GEOID_2010_trt" == "GEOID10")) %>%
unite("county_fips", FIPS_st, FIPS_county, sep = "")
svi_divisional_nmtc_df <- left_join(svi_divisional_nmtc_df1, msa_csa_crosswalk, join_by("county_fips" == "county_fips"))
svi_divisional_nmtc_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | county_fips | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | nmtc_eligibility | pre10_nmtc_project_cnt | pre10_nmtc_dollars | pre10_nmtc_dollars_formatted | post10_nmtc_project_cnt | post10_nmtc_dollars | post10_nmtc_dollars_formatted | nmtc_flag | NAME | Median_Income_10 | Median_Home_Value_10 | Median_Income_19 | Median_Home_Value_19 | Median_Income_10adj | Median_Home_Value_10adj | Median_Income_Change | Median_Income_Change_pct | Median_Home_Value_Change | Median_Home_Value_Change_pct | housing_price_index10 | housing_price_index20 | county_title | cbsa | cbsa_code |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 04001942600 | 04001 | 942600 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 1561 | 762 | 384 | 1150 | 1561 | 73.67072 | 0.9944 | 1 | 26 | 300 | 8.666667 | 0.6866 | 0 | 65 | 366 | 17.759563 | 0.101800 | 0 | 5 | 18 | 27.77778 | 0.19090 | 0 | 70 | 384 | 18.229167 | 0.057810 | 0 | 303 | 839 | 36.11442 | 0.9335 | 1 | 282 | 1578 | 17.87072 | 0.5921 | 0 | 153 | 9.801409 | 0.4496 | 0 | 560 | 35.87444 | 0.9044 | 1 | 240 | 1054 | 22.770398 | 0.9006 | 1 | 107 | 332 | 32.22892 | 0.9163 | 1 | 168 | 1431 | 11.740042 | 0.8831 | 1 | 1561 | 1561 | 100.00000 | 0.9989 | 1 | 762 | 0 | 0.0000000 | 0.1526 | 0 | 215 | 28.21522 | 0.9088 | 1 | 117 | 384 | 30.46875 | 0.9979 | 1 | 33 | 384 | 8.593750 | 0.7842 | 1 | 0 | 1561 | 0.000000 | 0.3955 | 0 | 3.264410 | 0.7248 | 2 | 4.0540 | 0.9853 | 4 | 0.9989 | 0.9931 | 1 | 3.2390 | 0.8004 | 3 | 11.55631 | 0.8966 | 10 | 1711 | 676 | 469 | 930 | 1711 | 54.35418 | 0.9708 | 1 | 44 | 484 | 9.090909 | 0.8539 | 1 | 32 | 456 | 7.017544 | 0.02013 | 0 | 4 | 13 | 30.769231 | 0.24630 | 0 | 36 | 469 | 7.675906 | 0.005758 | 0 | 304 | 1197 | 25.39683 | 0.9056 | 1 | 686 | 1711 | 40.09351 | 0.9973 | 1 | 229 | 13.38399 | 0.4397 | 0 | 347 | 20.28054 | 0.3788 | 0 | 245 | 1363.979 | 17.962156 | 0.68240 | 0 | 49 | 304.0000 | 16.11842 | 0.5859 | 0 | 155 | 1652 | 9.382567 | 0.8951 | 1 | 1711 | 1710.980 | 100.00115 | 1.0000 | 1 | 676 | 0 | 0.0000000 | 0.1276 | 0 | 142 | 21.00592 | 0.8736 | 1 | 83 | 469 | 17.697228 | 0.9774 | 1 | 99 | 469.000 | 21.10874 | 0.9655 | 1 | 0 | 1711 | 0.0000000 | 0.2155 | 0 | 3.733358 | 0.8474 | 4 | 2.98190 | 0.7375 | 1 | 1.0000 | 0.9958 | 1 | 3.1596 | 0.7653 | 3 | 10.87486 | 0.8573 | 9 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9426, Apache County, Arizona | 10268 | 27600 | 15822 | 45700 | 11910.88 | 32016 | 3911.12 | 0.3283653 | 13684 | 0.4274113 | NA | NA | NA | NA | NA |
| 04001942700 | 04001 | 942700 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4886 | 2757 | 1291 | 2616 | 4871 | 53.70560 | 0.9480 | 1 | 163 | 1398 | 11.659514 | 0.8577 | 1 | 102 | 1113 | 9.164421 | 0.017570 | 0 | 54 | 178 | 30.33708 | 0.22790 | 0 | 156 | 1291 | 12.083656 | 0.016520 | 0 | 1039 | 2931 | 35.44865 | 0.9303 | 1 | 1873 | 5249 | 35.68299 | 0.9436 | 1 | 688 | 14.081048 | 0.6870 | 0 | 1530 | 31.31396 | 0.7718 | 1 | 772 | 3514 | 21.969266 | 0.8839 | 1 | 246 | 939 | 26.19808 | 0.8308 | 1 | 592 | 4631 | 12.783416 | 0.8975 | 1 | 4846 | 4886 | 99.18133 | 0.9946 | 1 | 2757 | 0 | 0.0000000 | 0.1526 | 0 | 369 | 13.38411 | 0.7652 | 1 | 240 | 1291 | 18.59024 | 0.9756 | 1 | 188 | 1291 | 14.562355 | 0.9015 | 1 | 0 | 4886 | 0.000000 | 0.3955 | 0 | 3.696120 | 0.8288 | 4 | 4.0710 | 0.9870 | 4 | 0.9946 | 0.9890 | 1 | 3.1904 | 0.7848 | 3 | 11.95212 | 0.9295 | 12 | 5469 | 2222 | 1462 | 2784 | 5469 | 50.90510 | 0.9557 | 1 | 358 | 1642 | 21.802680 | 0.9925 | 1 | 114 | 1151 | 9.904431 | 0.04797 | 0 | 58 | 311 | 18.649518 | 0.09477 | 0 | 172 | 1462 | 11.764706 | 0.023990 | 0 | 852 | 3274 | 26.02321 | 0.9120 | 1 | 1856 | 5466 | 33.95536 | 0.9919 | 1 | 759 | 13.87822 | 0.4657 | 0 | 1555 | 28.43299 | 0.7739 | 1 | 706 | 3911.002 | 18.051640 | 0.68720 | 0 | 257 | 1035.0004 | 24.83091 | 0.8039 | 1 | 396 | 5078 | 7.798346 | 0.8624 | 1 | 5420 | 5469.002 | 99.10401 | 0.9946 | 1 | 2222 | 0 | 0.0000000 | 0.1276 | 0 | 400 | 18.00180 | 0.8488 | 1 | 238 | 1462 | 16.279070 | 0.9710 | 1 | 175 | 1462.001 | 11.96990 | 0.8742 | 1 | 26 | 5469 | 0.4754068 | 0.6430 | 0 | 3.876090 | 0.8796 | 4 | 3.59310 | 0.9421 | 3 | 0.9946 | 0.9905 | 1 | 3.4646 | 0.8721 | 3 | 11.92839 | 0.9425 | 11 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9427, Apache County, Arizona | 14348 | 55900 | 18740 | 47200 | 16643.68 | 64844 | 2096.32 | 0.1259529 | -17644 | -0.2720992 | NA | NA | NA | NA | NA |
| 04001944000 | 04001 | 944000 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 5958 | 2178 | 1275 | 3112 | 5958 | 52.23229 | 0.9399 | 1 | 107 | 1895 | 5.646438 | 0.4130 | 0 | 108 | 880 | 12.272727 | 0.034760 | 0 | 112 | 395 | 28.35443 | 0.19940 | 0 | 220 | 1275 | 17.254902 | 0.049550 | 0 | 1030 | 3376 | 30.50948 | 0.9015 | 1 | 2632 | 5821 | 45.21560 | 0.9873 | 1 | 472 | 7.922122 | 0.3301 | 0 | 1792 | 30.07721 | 0.7211 | 0 | 299 | 4027 | 7.424882 | 0.1343 | 0 | 272 | 979 | 27.78345 | 0.8590 | 1 | 153 | 5325 | 2.873239 | 0.6096 | 0 | 5846 | 5958 | 98.12017 | 0.9893 | 1 | 2178 | 0 | 0.0000000 | 0.1526 | 0 | 448 | 20.56933 | 0.8562 | 1 | 247 | 1275 | 19.37255 | 0.9798 | 1 | 135 | 1275 | 10.588235 | 0.8373 | 1 | 0 | 5958 | 0.000000 | 0.3955 | 0 | 3.291250 | 0.7314 | 3 | 2.6541 | 0.5792 | 1 | 0.9893 | 0.9836 | 1 | 3.2214 | 0.7946 | 3 | 10.15605 | 0.7714 | 8 | 6583 | 2464 | 1836 | 3270 | 6580 | 49.69605 | 0.9486 | 1 | 191 | 2029 | 9.413504 | 0.8663 | 1 | 89 | 1272 | 6.996855 | 0.01965 | 0 | 103 | 564 | 18.262411 | 0.09073 | 0 | 192 | 1836 | 10.457516 | 0.015550 | 0 | 753 | 4321 | 17.42652 | 0.8100 | 1 | 2993 | 6580 | 45.48632 | 0.9992 | 1 | 1034 | 15.70712 | 0.5561 | 0 | 1569 | 23.83412 | 0.5584 | 0 | 1069 | 5014.189 | 21.319499 | 0.81410 | 1 | 304 | 1237.2784 | 24.57006 | 0.7989 | 1 | 141 | 6193 | 2.276764 | 0.6147 | 0 | 6436 | 6583.375 | 97.76141 | 0.9876 | 1 | 2464 | 20 | 0.8116883 | 0.3404 | 0 | 536 | 21.75325 | 0.8793 | 1 | 274 | 1836 | 14.923747 | 0.9643 | 1 | 326 | 1836.376 | 17.75235 | 0.9488 | 1 | 3 | 6583 | 0.0455719 | 0.4382 | 0 | 3.639650 | 0.8211 | 4 | 3.34220 | 0.8770 | 2 | 0.9876 | 0.9834 | 1 | 3.5710 | 0.9020 | 3 | 11.54045 | 0.9156 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9440, Apache County, Arizona | 17679 | 61100 | 21541 | 40000 | 20507.64 | 70876 | 1033.36 | 0.0503890 | -30876 | -0.4356341 | NA | NA | NA | NA | NA |
| 04001944100 | 04001 | 944100 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4975 | 2485 | 1204 | 3251 | 4968 | 65.43881 | 0.9846 | 1 | 210 | 1254 | 16.746412 | 0.9576 | 1 | 122 | 905 | 13.480663 | 0.043830 | 0 | 91 | 299 | 30.43478 | 0.22960 | 0 | 213 | 1204 | 17.691030 | 0.053200 | 0 | 779 | 2325 | 33.50538 | 0.9203 | 1 | 1293 | 5511 | 23.46217 | 0.7705 | 1 | 344 | 6.914573 | 0.2701 | 0 | 1993 | 40.06030 | 0.9701 | 1 | 577 | 3087 | 18.691286 | 0.7799 | 1 | 278 | 893 | 31.13102 | 0.9038 | 1 | 308 | 4470 | 6.890380 | 0.7895 | 1 | 4915 | 4975 | 98.79397 | 0.9929 | 1 | 2485 | 21 | 0.8450704 | 0.3700 | 0 | 428 | 17.22334 | 0.8203 | 1 | 257 | 1204 | 21.34551 | 0.9843 | 1 | 212 | 1204 | 17.607973 | 0.9391 | 1 | 0 | 4975 | 0.000000 | 0.3955 | 0 | 3.686200 | 0.8261 | 4 | 3.7134 | 0.9528 | 4 | 0.9929 | 0.9872 | 1 | 3.5092 | 0.8926 | 3 | 11.90170 | 0.9244 | 12 | 6183 | 2379 | 1424 | 3704 | 5789 | 63.98342 | 0.9912 | 1 | 425 | 1608 | 26.430348 | 0.9954 | 1 | 132 | 1163 | 11.349957 | 0.07802 | 0 | 38 | 261 | 14.559387 | 0.06498 | 0 | 170 | 1424 | 11.938202 | 0.026300 | 0 | 862 | 3259 | 26.44983 | 0.9148 | 1 | 1320 | 6183 | 21.34886 | 0.9283 | 1 | 637 | 10.30244 | 0.2718 | 0 | 1869 | 30.22804 | 0.8396 | 1 | 626 | 3964.000 | 15.792129 | 0.57150 | 0 | 371 | 991.0000 | 37.43693 | 0.9557 | 1 | 315 | 5717 | 5.509883 | 0.8021 | 1 | 5981 | 6182.998 | 96.73300 | 0.9841 | 1 | 2379 | 0 | 0.0000000 | 0.1276 | 0 | 442 | 18.57924 | 0.8550 | 1 | 379 | 1424 | 26.615168 | 0.9969 | 1 | 347 | 1424.000 | 24.36798 | 0.9758 | 1 | 394 | 6183 | 6.3723112 | 0.9380 | 1 | 3.856000 | 0.8749 | 4 | 3.44070 | 0.9070 | 3 | 0.9841 | 0.9800 | 1 | 3.8933 | 0.9609 | 4 | 12.17410 | 0.9549 | 12 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9441, Apache County, Arizona | 13469 | 60900 | 16162 | 46800 | 15624.04 | 70644 | 537.96 | 0.0344316 | -23844 | -0.3375234 | NA | NA | NA | NA | NA |
| 04001944202 | 04001 | 944202 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 3330 | 1463 | 897 | 1814 | 3330 | 54.47447 | 0.9514 | 1 | 345 | 1024 | 33.691406 | 0.9983 | 1 | 58 | 745 | 7.785235 | 0.013520 | 0 | 38 | 152 | 25.00000 | 0.15680 | 0 | 96 | 897 | 10.702341 | 0.011910 | 0 | 742 | 2041 | 36.35473 | 0.9351 | 1 | 1201 | 3754 | 31.99254 | 0.9089 | 1 | 366 | 10.990991 | 0.5201 | 0 | 873 | 26.21622 | 0.5389 | 0 | 573 | 2986 | 19.189551 | 0.8002 | 1 | 151 | 550 | 27.45455 | 0.8540 | 1 | 173 | 3057 | 5.659143 | 0.7527 | 1 | 3306 | 3330 | 99.27928 | 0.9948 | 1 | 1463 | 0 | 0.0000000 | 0.1526 | 0 | 355 | 24.26521 | 0.8840 | 1 | 114 | 897 | 12.70903 | 0.9435 | 1 | 257 | 897 | 28.651059 | 0.9864 | 1 | 93 | 3330 | 2.792793 | 0.8680 | 1 | 3.805610 | 0.8512 | 4 | 3.4659 | 0.8981 | 3 | 0.9948 | 0.9891 | 1 | 3.8345 | 0.9589 | 4 | 12.10081 | 0.9410 | 12 | 3507 | 1508 | 1209 | 2113 | 3507 | 60.25093 | 0.9862 | 1 | 145 | 1041 | 13.928914 | 0.9605 | 1 | 81 | 1040 | 7.788462 | 0.02620 | 0 | 26 | 169 | 15.384615 | 0.07170 | 0 | 107 | 1209 | 8.850290 | 0.008637 | 0 | 403 | 2250 | 17.91111 | 0.8195 | 1 | 1457 | 3507 | 41.54548 | 0.9985 | 1 | 390 | 11.12062 | 0.3153 | 0 | 974 | 27.77303 | 0.7446 | 0 | 114 | 2533.000 | 4.500592 | 0.01399 | 0 | 189 | 717.0000 | 26.35983 | 0.8350 | 1 | 389 | 3265 | 11.914242 | 0.9273 | 1 | 3499 | 3507.000 | 99.77188 | 0.9983 | 1 | 1508 | 26 | 1.7241379 | 0.4052 | 0 | 434 | 28.77984 | 0.9188 | 1 | 98 | 1209 | 8.105873 | 0.8737 | 1 | 146 | 1209.000 | 12.07610 | 0.8761 | 1 | 0 | 3507 | 0.0000000 | 0.2155 | 0 | 3.773337 | 0.8552 | 4 | 2.83619 | 0.6678 | 2 | 0.9983 | 0.9941 | 1 | 3.2893 | 0.8112 | 3 | 10.89713 | 0.8589 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9442.02, Apache County, Arizona | 11741 | 53100 | 16052 | 25400 | 13619.56 | 61596 | 2432.44 | 0.1785990 | -36196 | -0.5876356 | NA | NA | NA | NA | NA |
| 04001944300 | 04001 | 944300 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 6806 | 3308 | 1826 | 4099 | 6797 | 60.30602 | 0.9762 | 1 | 403 | 1777 | 22.678672 | 0.9858 | 1 | 154 | 1457 | 10.569664 | 0.025490 | 0 | 63 | 369 | 17.07317 | 0.08684 | 0 | 217 | 1826 | 11.883899 | 0.015360 | 0 | 1432 | 3367 | 42.53044 | 0.9623 | 1 | 2305 | 7092 | 32.50141 | 0.9160 | 1 | 746 | 10.960917 | 0.5176 | 0 | 2767 | 40.65530 | 0.9761 | 1 | 842 | 4361 | 19.307498 | 0.8041 | 1 | 357 | 1163 | 30.69647 | 0.8982 | 1 | 568 | 6178 | 9.193914 | 0.8423 | 1 | 6750 | 6806 | 99.17720 | 0.9944 | 1 | 3308 | 8 | 0.2418380 | 0.3113 | 0 | 440 | 13.30109 | 0.7638 | 1 | 404 | 1826 | 22.12486 | 0.9856 | 1 | 388 | 1826 | 21.248631 | 0.9627 | 1 | 139 | 6806 | 2.042316 | 0.8458 | 1 | 3.855660 | 0.8602 | 4 | 4.0383 | 0.9844 | 4 | 0.9944 | 0.9888 | 1 | 3.8692 | 0.9619 | 4 | 12.75756 | 0.9749 | 13 | 5922 | 2801 | 2026 | 3548 | 5916 | 59.97295 | 0.9854 | 1 | 67 | 1402 | 4.778887 | 0.5316 | 0 | 251 | 1664 | 15.084135 | 0.20570 | 0 | 46 | 362 | 12.707182 | 0.05498 | 0 | 297 | 2026 | 14.659427 | 0.056430 | 0 | 844 | 3696 | 22.83550 | 0.8792 | 1 | 2528 | 5916 | 42.73158 | 0.9987 | 1 | 793 | 13.39075 | 0.4401 | 0 | 1663 | 28.08173 | 0.7575 | 1 | 573 | 4258.743 | 13.454674 | 0.42530 | 0 | 301 | 1112.2581 | 27.06206 | 0.8474 | 1 | 851 | 5568 | 15.283764 | 0.9575 | 1 | 5880 | 5922.449 | 99.28326 | 0.9964 | 1 | 2801 | 22 | 0.7854338 | 0.3369 | 0 | 521 | 18.60050 | 0.8557 | 1 | 267 | 2026 | 13.178677 | 0.9482 | 1 | 297 | 2025.690 | 14.66167 | 0.9158 | 1 | 11 | 5922 | 0.1857481 | 0.5222 | 0 | 3.451330 | 0.7773 | 3 | 3.42780 | 0.9008 | 3 | 0.9964 | 0.9922 | 1 | 3.5788 | 0.9040 | 3 | 11.45433 | 0.9088 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9443, Apache County, Arizona | 11133 | 48700 | 15051 | 53700 | 12914.28 | 56492 | 2136.72 | 0.1654541 | -2792 | -0.0494229 | NA | NA | NA | NA | NA |
| 04001944901 | 04001 | 944901 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 3538 | 2001 | 868 | 2034 | 3506 | 58.01483 | 0.9664 | 1 | 153 | 926 | 16.522678 | 0.9551 | 1 | 68 | 621 | 10.950081 | 0.027230 | 0 | 47 | 247 | 19.02834 | 0.10240 | 0 | 115 | 868 | 13.248848 | 0.023430 | 0 | 615 | 1757 | 35.00285 | 0.9280 | 1 | 1204 | 3723 | 32.33951 | 0.9127 | 1 | 409 | 11.560204 | 0.5556 | 0 | 1406 | 39.73997 | 0.9672 | 1 | 598 | 2467 | 24.239968 | 0.9257 | 1 | 181 | 629 | 28.77583 | 0.8759 | 1 | 244 | 3213 | 7.594149 | 0.8079 | 1 | 3491 | 3538 | 98.67157 | 0.9923 | 1 | 2001 | 0 | 0.0000000 | 0.1526 | 0 | 269 | 13.44328 | 0.7659 | 1 | 206 | 868 | 23.73272 | 0.9887 | 1 | 112 | 868 | 12.903226 | 0.8773 | 1 | 0 | 3538 | 0.000000 | 0.3955 | 0 | 3.785630 | 0.8476 | 4 | 4.1323 | 0.9882 | 4 | 0.9923 | 0.9867 | 1 | 3.1800 | 0.7807 | 3 | 12.09023 | 0.9402 | 12 | 4008 | 1775 | 1127 | 2545 | 4008 | 63.49800 | 0.9902 | 1 | 43 | 1000 | 4.300000 | 0.4727 | 0 | 70 | 946 | 7.399577 | 0.02292 | 0 | 14 | 181 | 7.734807 | 0.03172 | 0 | 84 | 1127 | 7.453416 | 0.005182 | 0 | 558 | 2312 | 24.13495 | 0.8942 | 1 | 598 | 4008 | 14.92016 | 0.8150 | 1 | 446 | 11.12774 | 0.3160 | 0 | 1361 | 33.95709 | 0.9342 | 1 | 393 | 2647.000 | 14.846997 | 0.51690 | 0 | 276 | 723.0000 | 38.17427 | 0.9599 | 1 | 177 | 3788 | 4.672650 | 0.7720 | 1 | 3957 | 4008.000 | 98.72754 | 0.9920 | 1 | 1775 | 0 | 0.0000000 | 0.1276 | 0 | 393 | 22.14085 | 0.8824 | 1 | 234 | 1127 | 20.763088 | 0.9868 | 1 | 280 | 1127.000 | 24.84472 | 0.9785 | 1 | 1 | 4008 | 0.0249501 | 0.4340 | 0 | 3.177282 | 0.7088 | 3 | 3.49900 | 0.9216 | 3 | 0.9920 | 0.9878 | 1 | 3.4093 | 0.8520 | 3 | 11.07758 | 0.8758 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9449.01, Apache County, Arizona | 13033 | 60200 | 20349 | 38200 | 15118.28 | 69832 | 5230.72 | 0.3459864 | -31632 | -0.4529728 | NA | NA | NA | NA | NA |
| 04001944902 | 04001 | 944902 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 6532 | 2589 | 1471 | 4250 | 6532 | 65.06430 | 0.9841 | 1 | 564 | 1838 | 30.685528 | 0.9971 | 1 | 94 | 1267 | 7.419100 | 0.012740 | 0 | 38 | 204 | 18.62745 | 0.09853 | 0 | 132 | 1471 | 8.973487 | 0.007874 | 0 | 1496 | 3893 | 38.42795 | 0.9450 | 1 | 1637 | 5606 | 29.20086 | 0.8785 | 1 | 751 | 11.497244 | 0.5527 | 0 | 1893 | 28.98040 | 0.6741 | 0 | 919 | 3843 | 23.913609 | 0.9204 | 1 | 217 | 969 | 22.39422 | 0.7518 | 1 | 934 | 6035 | 15.476388 | 0.9216 | 1 | 6415 | 6532 | 98.20882 | 0.9902 | 1 | 2589 | 7 | 0.2703747 | 0.3137 | 0 | 347 | 13.40286 | 0.7654 | 1 | 304 | 1471 | 20.66621 | 0.9833 | 1 | 418 | 1471 | 28.416044 | 0.9858 | 1 | 767 | 6532 | 11.742192 | 0.9557 | 1 | 3.812574 | 0.8526 | 4 | 3.8206 | 0.9657 | 3 | 0.9902 | 0.9846 | 1 | 4.0039 | 0.9775 | 4 | 12.62727 | 0.9703 | 12 | 4952 | 2210 | 1419 | 3101 | 4952 | 62.62116 | 0.9887 | 1 | 130 | 1341 | 9.694258 | 0.8776 | 1 | 128 | 1299 | 9.853734 | 0.04623 | 0 | 11 | 120 | 9.166667 | 0.03614 | 0 | 139 | 1419 | 9.795631 | 0.011710 | 0 | 759 | 3361 | 22.58256 | 0.8769 | 1 | 983 | 4952 | 19.85057 | 0.9107 | 1 | 759 | 15.32714 | 0.5379 | 0 | 1115 | 22.51616 | 0.4881 | 0 | 720 | 3837.257 | 18.763404 | 0.72230 | 0 | 232 | 934.7419 | 24.81969 | 0.8037 | 1 | 342 | 4667 | 7.328048 | 0.8515 | 1 | 4915 | 4951.551 | 99.26182 | 0.9962 | 1 | 2210 | 0 | 0.0000000 | 0.1276 | 0 | 404 | 18.28054 | 0.8519 | 1 | 287 | 1419 | 20.225511 | 0.9850 | 1 | 404 | 1419.310 | 28.46453 | 0.9881 | 1 | 25 | 4952 | 0.5048465 | 0.6529 | 0 | 3.665610 | 0.8272 | 4 | 3.40350 | 0.8950 | 2 | 0.9962 | 0.9920 | 1 | 3.6055 | 0.9109 | 3 | 11.67081 | 0.9240 | 10 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9449.02, Apache County, Arizona | 9837 | 64500 | 17988 | 30300 | 11410.92 | 74820 | 6577.08 | 0.5763847 | -44520 | -0.5950281 | NA | NA | NA | NA | NA |
| 04001945001 | 04001 | 945001 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4746 | 1477 | 993 | 2072 | 4523 | 45.81030 | 0.8983 | 1 | 210 | 1440 | 14.583333 | 0.9298 | 1 | 23 | 435 | 5.287356 | 0.008689 | 0 | 203 | 558 | 36.37993 | 0.34020 | 0 | 226 | 993 | 22.759315 | 0.129200 | 0 | 272 | 2249 | 12.09426 | 0.5906 | 0 | 1244 | 4576 | 27.18531 | 0.8446 | 1 | 195 | 4.108723 | 0.1071 | 0 | 1806 | 38.05310 | 0.9454 | 1 | 397 | 3289 | 12.070538 | 0.4212 | 0 | 294 | 722 | 40.72022 | 0.9743 | 1 | 37 | 4167 | 0.887929 | 0.3569 | 0 | 4676 | 4746 | 98.52507 | 0.9914 | 1 | 1477 | 0 | 0.0000000 | 0.1526 | 0 | 365 | 24.71225 | 0.8873 | 1 | 140 | 993 | 14.09869 | 0.9529 | 1 | 36 | 993 | 3.625378 | 0.5120 | 0 | 271 | 4746 | 5.710072 | 0.9170 | 1 | 3.392500 | 0.7522 | 3 | 2.8049 | 0.6463 | 2 | 0.9914 | 0.9857 | 1 | 3.4218 | 0.8668 | 3 | 10.61060 | 0.8171 | 9 | 4085 | 1794 | 1251 | 1170 | 3940 | 29.69543 | 0.7399 | 0 | 56 | 1640 | 3.414634 | 0.3522 | 0 | 69 | 759 | 9.090909 | 0.03679 | 0 | 22 | 492 | 4.471545 | 0.02268 | 0 | 91 | 1251 | 7.274181 | 0.004990 | 0 | 364 | 2717 | 13.39713 | 0.7250 | 0 | 975 | 4058 | 24.02661 | 0.9538 | 1 | 476 | 11.65239 | 0.3461 | 0 | 1006 | 24.62668 | 0.5988 | 0 | 484 | 3059.000 | 15.822164 | 0.57440 | 0 | 185 | 787.0000 | 23.50699 | 0.7766 | 1 | 59 | 3882 | 1.519835 | 0.5168 | 0 | 4012 | 4085.000 | 98.21297 | 0.9902 | 1 | 1794 | 0 | 0.0000000 | 0.1276 | 0 | 395 | 22.01784 | 0.8814 | 1 | 182 | 1251 | 14.548361 | 0.9626 | 1 | 141 | 1251.000 | 11.27098 | 0.8621 | 1 | 77 | 4085 | 1.8849449 | 0.8277 | 1 | 2.775890 | 0.5926 | 1 | 2.81270 | 0.6550 | 1 | 0.9902 | 0.9861 | 1 | 3.6614 | 0.9221 | 4 | 10.24019 | 0.7910 | 7 | Yes | 0 | 0 | $0 | 1 | 12544000 | $12,544,000 | 1 | Census Tract 9450.01, Apache County, Arizona | 13049 | 50500 | 25587 | 66700 | 15136.84 | 58580 | 10450.16 | 0.6903792 | 8120 | 0.1386139 | NA | NA | NA | NA | NA |
| 04001945002 | 04001 | 945002 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4093 | 1831 | 1075 | 2257 | 4093 | 55.14293 | 0.9553 | 1 | 66 | 1026 | 6.432748 | 0.4929 | 0 | 140 | 968 | 14.462810 | 0.054450 | 0 | 21 | 107 | 19.62617 | 0.10760 | 0 | 161 | 1075 | 14.976744 | 0.033030 | 0 | 698 | 2337 | 29.86735 | 0.8977 | 1 | 1357 | 4258 | 31.86942 | 0.9075 | 1 | 449 | 10.969949 | 0.5188 | 0 | 1355 | 33.10530 | 0.8284 | 1 | 428 | 3071 | 13.936828 | 0.5396 | 0 | 173 | 677 | 25.55391 | 0.8189 | 1 | 232 | 3846 | 6.032241 | 0.7667 | 1 | 4083 | 4093 | 99.75568 | 0.9971 | 1 | 1831 | 0 | 0.0000000 | 0.1526 | 0 | 333 | 18.18678 | 0.8305 | 1 | 261 | 1075 | 24.27907 | 0.9898 | 1 | 292 | 1075 | 27.162791 | 0.9835 | 1 | 0 | 4093 | 0.000000 | 0.3955 | 0 | 3.286430 | 0.7303 | 3 | 3.4724 | 0.8998 | 3 | 0.9971 | 0.9914 | 1 | 3.3519 | 0.8430 | 3 | 11.10783 | 0.8573 | 10 | 4053 | 1729 | 1156 | 2013 | 4050 | 49.70370 | 0.9488 | 1 | 136 | 1268 | 10.725552 | 0.9064 | 1 | 68 | 1072 | 6.343284 | 0.01445 | 0 | 9 | 84 | 10.714286 | 0.04296 | 0 | 77 | 1156 | 6.660900 | 0.004223 | 0 | 607 | 2836 | 21.40339 | 0.8655 | 1 | 1166 | 4053 | 28.76881 | 0.9803 | 1 | 550 | 13.57019 | 0.4498 | 0 | 869 | 21.44091 | 0.4357 | 0 | 488 | 3184.000 | 15.326633 | 0.54540 | 0 | 224 | 763.0000 | 29.35780 | 0.8826 | 1 | 84 | 3910 | 2.148338 | 0.6005 | 0 | 3971 | 4053.000 | 97.97681 | 0.9885 | 1 | 1729 | 0 | 0.0000000 | 0.1276 | 0 | 471 | 27.24118 | 0.9100 | 1 | 280 | 1156 | 24.221453 | 0.9944 | 1 | 197 | 1156.000 | 17.04152 | 0.9413 | 1 | 6 | 4053 | 0.1480385 | 0.4982 | 0 | 3.705223 | 0.8383 | 4 | 2.91400 | 0.7057 | 1 | 0.9885 | 0.9844 | 1 | 3.4715 | 0.8754 | 3 | 11.07922 | 0.8760 | 9 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 9450.02, Apache County, Arizona | 12308 | 56600 | 20899 | 34700 | 14277.28 | 65656 | 6621.72 | 0.4637942 | -30956 | -0.4714878 | NA | NA | NA | NA | NA |
National
svi_national_nmtc_df0 <- left_join(svi_national_nmtc, census_pull_df, join_by("GEOID_2010_trt" == "GEOID"))
svi_national_nmtc_df1 <- left_join(svi_national_nmtc_df0, hpi_df_10_20, join_by("GEOID_2010_trt" == "GEOID10")) %>%
unite("county_fips", FIPS_st, FIPS_county, sep = "")
svi_national_nmtc_df <- left_join(svi_national_nmtc_df1, msa_csa_crosswalk, join_by("county_fips" == "county_fips"))
svi_national_nmtc_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | county_fips | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | nmtc_eligibility | pre10_nmtc_project_cnt | pre10_nmtc_dollars | pre10_nmtc_dollars_formatted | post10_nmtc_project_cnt | post10_nmtc_dollars | post10_nmtc_dollars_formatted | nmtc_flag | NAME | Median_Income_10 | Median_Home_Value_10 | Median_Income_19 | Median_Home_Value_19 | Median_Income_10adj | Median_Home_Value_10adj | Median_Income_Change | Median_Income_Change_pct | Median_Home_Value_Change | Median_Home_Value_Change_pct | housing_price_index10 | housing_price_index20 | county_title | cbsa | cbsa_code |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01001020200 | 01001 | 020200 | AL | Alabama | Autauga County | 3 | South Region | 6 | East South Central Division | 2020 | 816 | 730 | 495 | 1992 | 24.84940 | 0.5954 | 0 | 68 | 834 | 8.153477 | 0.57540 | 0 | 49 | 439 | 11.16173 | 0.02067 | 0 | 105 | 291 | 36.08247 | 0.30190 | 0 | 154 | 730 | 21.09589 | 0.09312 | 0 | 339 | 1265 | 26.798419 | 0.8392 | 1 | 313 | 2012 | 15.55666 | 0.6000 | 0 | 204 | 10.09901 | 0.3419 | 0 | 597 | 29.55446 | 0.8192 | 1 | 359 | 1515 | 23.69637 | 0.8791 | 1 | 132 | 456 | 28.947368 | 0.8351 | 1 | 15 | 1890 | 0.7936508 | 0.40130 | 0 | 1243 | 2020 | 61.534653 | 0.77810 | 1 | 816 | 0 | 0.0000000 | 0.1224 | 0 | 34 | 4.1666667 | 0.6664 | 0 | 13 | 730 | 1.780822 | 0.5406 | 0 | 115 | 730 | 15.7534247 | 0.83820 | 1 | 0 | 2020 | 0.0000 | 0.3640 | 0 | 2.70312 | 0.5665 | 1 | 3.27660 | 0.8614 | 3 | 0.77810 | 0.7709 | 1 | 2.53160 | 0.5047 | 1 | 9.28942 | 0.6832 | 6 | 1757 | 720 | 573 | 384 | 1511 | 25.413633 | 0.6427 | 0 | 29 | 717 | 4.044630 | 0.41320 | 0 | 33 | 392 | 8.418367 | 0.03542 | 0 | 116 | 181 | 64.08840 | 0.9086 | 1 | 149 | 573 | 26.00349 | 0.40410 | 0 | 139 | 1313 | 10.586443 | 0.5601 | 0 | 91 | 1533 | 5.936073 | 0.4343 | 0 | 284 | 16.163916 | 0.5169 | 0 | 325 | 18.49744 | 0.28510 | 0 | 164 | 1208.000 | 13.576159 | 0.4127 | 0 | 42 | 359.0000 | 11.6991643 | 0.39980 | 0 | 0 | 1651 | 0.0000000 | 0.09479 | 0 | 1116 | 1757.000 | 63.5173591 | 0.759100 | 1 | 720 | 3 | 0.4166667 | 0.2470 | 0 | 5 | 0.6944444 | 0.5106 | 0 | 9 | 573 | 1.5706806 | 0.46880 | 0 | 57 | 573.000 | 9.947644 | 0.7317 | 0 | 212 | 1757 | 12.0660216 | 0.9549 | 1 | 2.45440 | 0.4888 | 0 | 1.70929 | 0.10250 | 0 | 0.759100 | 0.752700 | 1 | 2.91300 | 0.6862 | 1 | 7.835790 | 0.4802 | 2 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 202, Autauga County, Alabama | 19437 | 138500 | 20154 | 90500 | 22546.92 | 160660 | -2392.92 | -0.1061307 | -70160 | -0.4366986 | 123.78 | 123.37 | Autauga County, Alabama | Montgomery-Alexander City, AL CSA | CS388 |
| 01001020700 | 01001 | 020700 | AL | Alabama | Autauga County | 3 | South Region | 6 | East South Central Division | 2664 | 1254 | 1139 | 710 | 2664 | 26.65165 | 0.6328 | 0 | 29 | 1310 | 2.213741 | 0.05255 | 0 | 134 | 710 | 18.87324 | 0.13890 | 0 | 187 | 429 | 43.58974 | 0.47090 | 0 | 321 | 1139 | 28.18262 | 0.28130 | 0 | 396 | 1852 | 21.382289 | 0.7478 | 0 | 345 | 2878 | 11.98749 | 0.4459 | 0 | 389 | 14.60210 | 0.6417 | 0 | 599 | 22.48499 | 0.4007 | 0 | 510 | 2168 | 23.52399 | 0.8752 | 1 | 228 | 712 | 32.022472 | 0.8712 | 1 | 0 | 2480 | 0.0000000 | 0.09298 | 0 | 694 | 2664 | 26.051051 | 0.51380 | 0 | 1254 | 8 | 0.6379585 | 0.2931 | 0 | 460 | 36.6826156 | 0.9714 | 1 | 0 | 1139 | 0.000000 | 0.1238 | 0 | 125 | 1139 | 10.9745391 | 0.74770 | 0 | 0 | 2664 | 0.0000 | 0.3640 | 0 | 2.16035 | 0.4069 | 0 | 2.88178 | 0.6997 | 2 | 0.51380 | 0.5090 | 0 | 2.50000 | 0.4882 | 1 | 8.05593 | 0.5185 | 3 | 3562 | 1313 | 1248 | 1370 | 3528 | 38.832200 | 0.8512 | 1 | 128 | 1562 | 8.194622 | 0.79350 | 1 | 168 | 844 | 19.905213 | 0.44510 | 0 | 237 | 404 | 58.66337 | 0.8359 | 1 | 405 | 1248 | 32.45192 | 0.60420 | 0 | 396 | 2211 | 17.910448 | 0.7857 | 1 | 444 | 3547 | 12.517620 | 0.7758 | 1 | 355 | 9.966311 | 0.1800 | 0 | 954 | 26.78271 | 0.79230 | 1 | 629 | 2593.000 | 24.257617 | 0.8730 | 1 | 171 | 797.0000 | 21.4554580 | 0.71860 | 0 | 0 | 3211 | 0.0000000 | 0.09479 | 0 | 1009 | 3562.000 | 28.3267827 | 0.466800 | 0 | 1313 | 14 | 1.0662605 | 0.3165 | 0 | 443 | 33.7395278 | 0.9663 | 1 | 73 | 1248 | 5.8493590 | 0.82110 | 1 | 17 | 1248.000 | 1.362180 | 0.1554 | 0 | 112 | 3562 | 3.1443010 | 0.8514 | 1 | 3.81040 | 0.8569 | 4 | 2.65869 | 0.58470 | 2 | 0.466800 | 0.462900 | 0 | 3.11070 | 0.7714 | 3 | 10.046590 | 0.7851 | 9 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 207, Autauga County, Alabama | 22114 | 93800 | 20934 | 82400 | 25652.24 | 108808 | -4718.24 | -0.1839309 | -26408 | -0.2427027 | 95.94 | 108.47 | Autauga County, Alabama | Montgomery-Alexander City, AL CSA | CS388 |
| 01001021100 | 01001 | 021100 | AL | Alabama | Autauga County | 3 | South Region | 6 | East South Central Division | 3298 | 1502 | 1323 | 860 | 3298 | 26.07641 | 0.6211 | 0 | 297 | 1605 | 18.504673 | 0.94340 | 1 | 250 | 1016 | 24.60630 | 0.32070 | 0 | 74 | 307 | 24.10423 | 0.11920 | 0 | 324 | 1323 | 24.48980 | 0.17380 | 0 | 710 | 2231 | 31.824294 | 0.8976 | 1 | 654 | 3565 | 18.34502 | 0.7018 | 0 | 411 | 12.46210 | 0.5001 | 0 | 738 | 22.37720 | 0.3934 | 0 | 936 | 2861 | 32.71583 | 0.9807 | 1 | 138 | 825 | 16.727273 | 0.5715 | 0 | 9 | 3155 | 0.2852615 | 0.25010 | 0 | 1979 | 3298 | 60.006064 | 0.77030 | 1 | 1502 | 14 | 0.9320905 | 0.3234 | 0 | 659 | 43.8748336 | 0.9849 | 1 | 44 | 1323 | 3.325775 | 0.7062 | 0 | 137 | 1323 | 10.3552532 | 0.73130 | 0 | 0 | 3298 | 0.0000 | 0.3640 | 0 | 3.33770 | 0.7351 | 2 | 2.69580 | 0.6028 | 1 | 0.77030 | 0.7631 | 1 | 3.10980 | 0.7827 | 1 | 9.91360 | 0.7557 | 5 | 3499 | 1825 | 1462 | 1760 | 3499 | 50.300086 | 0.9396 | 1 | 42 | 966 | 4.347826 | 0.45390 | 0 | 426 | 1274 | 33.437991 | 0.85200 | 1 | 52 | 188 | 27.65957 | 0.1824 | 0 | 478 | 1462 | 32.69494 | 0.61110 | 0 | 422 | 2488 | 16.961415 | 0.7638 | 1 | 497 | 3499 | 14.204058 | 0.8246 | 1 | 853 | 24.378394 | 0.8688 | 1 | 808 | 23.09231 | 0.58290 | 0 | 908 | 2691.100 | 33.740844 | 0.9808 | 1 | 179 | 811.6985 | 22.0525243 | 0.73230 | 0 | 8 | 3248 | 0.2463054 | 0.26220 | 0 | 1986 | 3498.713 | 56.7637257 | 0.717500 | 0 | 1825 | 29 | 1.5890411 | 0.3551 | 0 | 576 | 31.5616438 | 0.9594 | 1 | 88 | 1462 | 6.0191518 | 0.82690 | 1 | 148 | 1461.993 | 10.123166 | 0.7364 | 0 | 38 | 3499 | 1.0860246 | 0.7013 | 0 | 3.59300 | 0.8073 | 3 | 3.42700 | 0.91560 | 2 | 0.717500 | 0.711400 | 0 | 3.57910 | 0.9216 | 2 | 11.316600 | 0.9150 | 7 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 211, Autauga County, Alabama | 17997 | 74000 | 20620 | 88600 | 20876.52 | 85840 | -256.52 | -0.0122875 | 2760 | 0.0321528 | 134.13 | 145.41 | Autauga County, Alabama | Montgomery-Alexander City, AL CSA | CS388 |
| 01003010200 | 01003 | 010200 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 2612 | 1220 | 1074 | 338 | 2605 | 12.97505 | 0.2907 | 0 | 44 | 1193 | 3.688181 | 0.14720 | 0 | 172 | 928 | 18.53448 | 0.13090 | 0 | 31 | 146 | 21.23288 | 0.09299 | 0 | 203 | 1074 | 18.90130 | 0.05657 | 0 | 455 | 1872 | 24.305556 | 0.8016 | 1 | 456 | 2730 | 16.70330 | 0.6445 | 0 | 401 | 15.35222 | 0.6847 | 0 | 563 | 21.55436 | 0.3406 | 0 | 410 | 2038 | 20.11776 | 0.7755 | 1 | 64 | 779 | 8.215661 | 0.2181 | 0 | 0 | 2510 | 0.0000000 | 0.09298 | 0 | 329 | 2612 | 12.595712 | 0.31130 | 0 | 1220 | 38 | 3.1147541 | 0.4648 | 0 | 385 | 31.5573770 | 0.9545 | 1 | 20 | 1074 | 1.862197 | 0.5509 | 0 | 43 | 1074 | 4.0037244 | 0.40880 | 0 | 0 | 2612 | 0.0000 | 0.3640 | 0 | 1.94057 | 0.3398 | 1 | 2.11188 | 0.2802 | 1 | 0.31130 | 0.3084 | 0 | 2.74300 | 0.6129 | 1 | 7.10675 | 0.3771 | 3 | 2928 | 1312 | 1176 | 884 | 2928 | 30.191257 | 0.7334 | 0 | 29 | 1459 | 1.987663 | 0.13560 | 0 | 71 | 830 | 8.554217 | 0.03726 | 0 | 134 | 346 | 38.72832 | 0.3964 | 0 | 205 | 1176 | 17.43197 | 0.12010 | 0 | 294 | 2052 | 14.327485 | 0.6940 | 0 | 219 | 2925 | 7.487179 | 0.5423 | 0 | 556 | 18.989071 | 0.6705 | 0 | 699 | 23.87295 | 0.63390 | 0 | 489 | 2226.455 | 21.963167 | 0.8122 | 1 | 191 | 783.8820 | 24.3659136 | 0.77990 | 1 | 0 | 2710 | 0.0000000 | 0.09479 | 0 | 398 | 2927.519 | 13.5951280 | 0.251100 | 0 | 1312 | 13 | 0.9908537 | 0.3111 | 0 | 400 | 30.4878049 | 0.9557 | 1 | 6 | 1176 | 0.5102041 | 0.25900 | 0 | 81 | 1176.202 | 6.886570 | 0.6115 | 0 | 7 | 2928 | 0.2390710 | 0.4961 | 0 | 2.22540 | 0.4183 | 0 | 2.99129 | 0.76340 | 2 | 0.251100 | 0.249000 | 0 | 2.63340 | 0.5496 | 1 | 8.101190 | 0.5207 | 3 | Yes | 0 | 0 | $0 | 1 | 408000 | $408,000 | 1 | Census Tract 102, Baldwin County, Alabama | 23862 | 103200 | 26085 | 136900 | 27679.92 | 119712 | -1594.92 | -0.0576201 | 17188 | 0.1435779 | 128.38 | 166.27 | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01003010500 | 01003 | 010500 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 4230 | 1779 | 1425 | 498 | 3443 | 14.46413 | 0.3337 | 0 | 166 | 1625 | 10.215385 | 0.71790 | 0 | 151 | 1069 | 14.12535 | 0.04638 | 0 | 196 | 356 | 55.05618 | 0.73830 | 0 | 347 | 1425 | 24.35088 | 0.17010 | 0 | 707 | 2945 | 24.006791 | 0.7967 | 1 | 528 | 4001 | 13.19670 | 0.5005 | 0 | 619 | 14.63357 | 0.6436 | 0 | 790 | 18.67612 | 0.1937 | 0 | 536 | 3096 | 17.31266 | 0.6572 | 0 | 165 | 920 | 17.934783 | 0.6102 | 0 | 20 | 4021 | 0.4973887 | 0.32320 | 0 | 754 | 4230 | 17.825059 | 0.40230 | 0 | 1779 | 97 | 5.4525014 | 0.5525 | 0 | 8 | 0.4496908 | 0.4600 | 0 | 63 | 1425 | 4.421053 | 0.7762 | 1 | 90 | 1425 | 6.3157895 | 0.56910 | 0 | 787 | 4230 | 18.6052 | 0.9649 | 1 | 2.51890 | 0.5121 | 1 | 2.42790 | 0.4539 | 0 | 0.40230 | 0.3986 | 0 | 3.32270 | 0.8628 | 2 | 8.67180 | 0.6054 | 3 | 5877 | 1975 | 1836 | 820 | 5244 | 15.636918 | 0.3902 | 0 | 90 | 2583 | 3.484321 | 0.33610 | 0 | 159 | 1345 | 11.821561 | 0.10530 | 0 | 139 | 491 | 28.30957 | 0.1924 | 0 | 298 | 1836 | 16.23094 | 0.09053 | 0 | 570 | 4248 | 13.418079 | 0.6669 | 0 | 353 | 5247 | 6.727654 | 0.4924 | 0 | 1109 | 18.870172 | 0.6645 | 0 | 1144 | 19.46571 | 0.34110 | 0 | 717 | 4102.545 | 17.476956 | 0.6332 | 0 | 103 | 1286.1180 | 8.0085961 | 0.23410 | 0 | 0 | 5639 | 0.0000000 | 0.09479 | 0 | 868 | 5877.481 | 14.7682323 | 0.270900 | 0 | 1975 | 26 | 1.3164557 | 0.3359 | 0 | 45 | 2.2784810 | 0.6271 | 0 | 9 | 1836 | 0.4901961 | 0.25400 | 0 | 116 | 1835.798 | 6.318779 | 0.5811 | 0 | 633 | 5877 | 10.7708014 | 0.9507 | 1 | 1.97613 | 0.3410 | 0 | 1.96769 | 0.19610 | 0 | 0.270900 | 0.268600 | 0 | 2.74880 | 0.6077 | 1 | 6.963520 | 0.3406 | 1 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 105, Baldwin County, Alabama | 21585 | 121100 | 28301 | 148500 | 25038.60 | 140476 | 3262.40 | 0.1302948 | 8024 | 0.0571201 | 191.57 | 213.49 | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01003010600 | 01003 | 010600 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 3724 | 1440 | 1147 | 1973 | 3724 | 52.98067 | 0.9342 | 1 | 142 | 1439 | 9.867964 | 0.69680 | 0 | 235 | 688 | 34.15698 | 0.62950 | 0 | 187 | 459 | 40.74074 | 0.40290 | 0 | 422 | 1147 | 36.79163 | 0.55150 | 0 | 497 | 1876 | 26.492537 | 0.8354 | 1 | 511 | 3661 | 13.95794 | 0.5334 | 0 | 246 | 6.60580 | 0.1481 | 0 | 1256 | 33.72718 | 0.9305 | 1 | 496 | 2522 | 19.66693 | 0.7587 | 1 | 274 | 838 | 32.696897 | 0.8779 | 1 | 32 | 3479 | 0.9198045 | 0.42810 | 0 | 2606 | 3724 | 69.978518 | 0.81840 | 1 | 1440 | 21 | 1.4583333 | 0.3683 | 0 | 321 | 22.2916667 | 0.9036 | 1 | 97 | 1147 | 8.456844 | 0.8956 | 1 | 167 | 1147 | 14.5597210 | 0.82090 | 1 | 0 | 3724 | 0.0000 | 0.3640 | 0 | 3.55130 | 0.7859 | 2 | 3.14330 | 0.8145 | 3 | 0.81840 | 0.8108 | 1 | 3.35240 | 0.8725 | 3 | 10.86540 | 0.8550 | 9 | 4115 | 1534 | 1268 | 1676 | 3997 | 41.931449 | 0.8814 | 1 | 294 | 1809 | 16.252073 | 0.96740 | 1 | 341 | 814 | 41.891892 | 0.94320 | 1 | 204 | 454 | 44.93392 | 0.5438 | 0 | 545 | 1268 | 42.98107 | 0.83620 | 1 | 624 | 2425 | 25.731959 | 0.9002 | 1 | 994 | 4115 | 24.155529 | 0.9602 | 1 | 642 | 15.601458 | 0.4841 | 0 | 1126 | 27.36331 | 0.81750 | 1 | 568 | 2989.000 | 19.003011 | 0.7045 | 0 | 212 | 715.0000 | 29.6503497 | 0.85920 | 1 | 56 | 3825 | 1.4640523 | 0.53120 | 0 | 2715 | 4115.000 | 65.9781288 | 0.773200 | 1 | 1534 | 0 | 0.0000000 | 0.1079 | 0 | 529 | 34.4850065 | 0.9685 | 1 | 101 | 1268 | 7.9652997 | 0.87950 | 1 | 89 | 1268.000 | 7.018927 | 0.6184 | 0 | 17 | 4115 | 0.4131227 | 0.5707 | 0 | 4.54540 | 0.9754 | 5 | 3.39650 | 0.90810 | 2 | 0.773200 | 0.766700 | 1 | 3.14500 | 0.7858 | 2 | 11.860100 | 0.9520 | 10 | Yes | 0 | 0 | $0 | 1 | 8000000 | $8,000,000 | 1 | Census Tract 106, Baldwin County, Alabama | 17788 | 81600 | 16453 | 104700 | 20634.08 | 94656 | -4181.08 | -0.2026298 | 10044 | 0.1061105 | NA | NA | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01003011000 | 01003 | 011000 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 3758 | 2012 | 1576 | 1053 | 3758 | 28.02022 | 0.6597 | 0 | 66 | 1707 | 3.866432 | 0.16250 | 0 | 293 | 1297 | 22.59059 | 0.25080 | 0 | 83 | 279 | 29.74910 | 0.19030 | 0 | 376 | 1576 | 23.85787 | 0.15710 | 0 | 744 | 2723 | 27.322806 | 0.8465 | 1 | 996 | 4137 | 24.07542 | 0.8462 | 1 | 713 | 18.97286 | 0.8429 | 1 | 804 | 21.39436 | 0.3306 | 0 | 763 | 3295 | 23.15630 | 0.8670 | 1 | 155 | 1145 | 13.537118 | 0.4538 | 0 | 50 | 3475 | 1.4388489 | 0.51460 | 0 | 516 | 3758 | 13.730708 | 0.33300 | 0 | 2012 | 0 | 0.0000000 | 0.1224 | 0 | 606 | 30.1192843 | 0.9484 | 1 | 42 | 1576 | 2.664975 | 0.6476 | 0 | 96 | 1576 | 6.0913706 | 0.55620 | 0 | 0 | 3758 | 0.0000 | 0.3640 | 0 | 2.67200 | 0.5579 | 2 | 3.00890 | 0.7581 | 2 | 0.33300 | 0.3299 | 0 | 2.63860 | 0.5614 | 1 | 8.65250 | 0.6030 | 5 | 4921 | 1979 | 1732 | 1539 | 4908 | 31.356968 | 0.7523 | 1 | 150 | 2105 | 7.125891 | 0.72850 | 0 | 214 | 1471 | 14.547927 | 0.20260 | 0 | 59 | 261 | 22.60536 | 0.1167 | 0 | 273 | 1732 | 15.76212 | 0.07981 | 0 | 936 | 3332 | 28.091237 | 0.9206 | 1 | 861 | 4921 | 17.496444 | 0.8930 | 1 | 1039 | 21.113595 | 0.7653 | 1 | 1183 | 24.03983 | 0.64410 | 0 | 585 | 3738.000 | 15.650080 | 0.5371 | 0 | 81 | 1151.0000 | 7.0373588 | 0.19000 | 0 | 101 | 4546 | 2.2217334 | 0.61440 | 0 | 1244 | 4921.000 | 25.2794148 | 0.427800 | 0 | 1979 | 0 | 0.0000000 | 0.1079 | 0 | 527 | 26.6296109 | 0.9393 | 1 | 83 | 1732 | 4.7921478 | 0.77460 | 1 | 151 | 1732.000 | 8.718245 | 0.6904 | 0 | 20 | 4921 | 0.4064215 | 0.5688 | 0 | 3.37421 | 0.7528 | 3 | 2.75090 | 0.63780 | 1 | 0.427800 | 0.424200 | 0 | 3.08100 | 0.7597 | 2 | 9.633910 | 0.7366 | 6 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 110, Baldwin County, Alabama | 19340 | 126400 | 23679 | 158700 | 22434.40 | 146624 | 1244.60 | 0.0554773 | 12076 | 0.0823603 | 129.69 | 188.85 | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01003011406 | 01003 | 011406 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 3317 | 6418 | 1307 | 583 | 3317 | 17.57612 | 0.4181 | 0 | 70 | 1789 | 3.912800 | 0.16690 | 0 | 221 | 685 | 32.26277 | 0.57540 | 0 | 284 | 622 | 45.65916 | 0.52130 | 0 | 505 | 1307 | 38.63810 | 0.60430 | 0 | 168 | 2255 | 7.450111 | 0.2800 | 0 | 919 | 3677 | 24.99320 | 0.8623 | 1 | 452 | 13.62677 | 0.5791 | 0 | 673 | 20.28942 | 0.2668 | 0 | 366 | 2769 | 13.21777 | 0.4276 | 0 | 96 | 887 | 10.822999 | 0.3359 | 0 | 180 | 3066 | 5.8708415 | 0.77920 | 1 | 473 | 3317 | 14.259873 | 0.34330 | 0 | 6418 | 3976 | 61.9507635 | 0.9655 | 1 | 384 | 5.9831723 | 0.7063 | 0 | 17 | 1307 | 1.300689 | 0.4632 | 0 | 10 | 1307 | 0.7651109 | 0.08684 | 0 | 0 | 3317 | 0.0000 | 0.3640 | 0 | 2.33160 | 0.4577 | 1 | 2.38860 | 0.4323 | 1 | 0.34330 | 0.3401 | 0 | 2.58584 | 0.5335 | 1 | 7.64934 | 0.4576 | 3 | 3226 | 7850 | 1797 | 228 | 3215 | 7.091757 | 0.1241 | 0 | 72 | 2055 | 3.503650 | 0.33910 | 0 | 302 | 1139 | 26.514486 | 0.69300 | 0 | 230 | 658 | 34.95441 | 0.3131 | 0 | 532 | 1797 | 29.60490 | 0.52020 | 0 | 128 | 2726 | 4.695525 | 0.2384 | 0 | 530 | 3226 | 16.429014 | 0.8749 | 1 | 790 | 24.488531 | 0.8715 | 1 | 342 | 10.60136 | 0.05624 | 0 | 280 | 2884.000 | 9.708738 | 0.1832 | 0 | 58 | 792.0000 | 7.3232323 | 0.20270 | 0 | 15 | 3107 | 0.4827808 | 0.34070 | 0 | 15 | 3226.000 | 0.4649721 | 0.002512 | 0 | 7850 | 5394 | 68.7133758 | 0.9706 | 1 | 274 | 3.4904459 | 0.6697 | 0 | 23 | 1797 | 1.2799110 | 0.41980 | 0 | 26 | 1797.000 | 1.446856 | 0.1647 | 0 | 0 | 3226 | 0.0000000 | 0.1831 | 0 | 2.09670 | 0.3785 | 1 | 1.65434 | 0.08785 | 1 | 0.002512 | 0.002491 | 0 | 2.40790 | 0.4381 | 1 | 6.161452 | 0.2215 | 3 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 114.06, Baldwin County, Alabama | 29838 | 252000 | 32201 | 224200 | 34612.08 | 292320 | -2411.08 | -0.0696601 | -68120 | -0.2330323 | NA | NA | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01003011407 | 01003 | 011407 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 5187 | 6687 | 2066 | 1404 | 5172 | 27.14617 | 0.6423 | 0 | 172 | 1935 | 8.888889 | 0.63280 | 0 | 482 | 1433 | 33.63573 | 0.61530 | 0 | 367 | 633 | 57.97788 | 0.79510 | 1 | 849 | 2066 | 41.09390 | 0.67110 | 0 | 278 | 3618 | 7.683803 | 0.2906 | 0 | 1027 | 4945 | 20.76845 | 0.7735 | 1 | 1398 | 26.95200 | 0.9629 | 1 | 1263 | 24.34933 | 0.5302 | 0 | 596 | 3792 | 15.71730 | 0.5759 | 0 | 158 | 1633 | 9.675444 | 0.2833 | 0 | 29 | 4867 | 0.5958496 | 0.35240 | 0 | 170 | 5187 | 3.277424 | 0.07984 | 0 | 6687 | 2772 | 41.4535666 | 0.9251 | 1 | 197 | 2.9460147 | 0.6326 | 0 | 90 | 2066 | 4.356244 | 0.7729 | 1 | 0 | 2066 | 0.0000000 | 0.02586 | 0 | 0 | 5187 | 0.0000 | 0.3640 | 0 | 3.01030 | 0.6516 | 1 | 2.70470 | 0.6077 | 1 | 0.07984 | 0.0791 | 0 | 2.72046 | 0.6014 | 2 | 8.51530 | 0.5852 | 4 | 5608 | 7576 | 2543 | 1058 | 5602 | 18.886112 | 0.4835 | 0 | 32 | 2631 | 1.216268 | 0.05882 | 0 | 581 | 1979 | 29.358262 | 0.77080 | 1 | 309 | 564 | 54.78723 | 0.7671 | 1 | 890 | 2543 | 34.99803 | 0.67250 | 0 | 230 | 4433 | 5.188360 | 0.2698 | 0 | 776 | 5602 | 13.852196 | 0.8156 | 1 | 1527 | 27.228959 | 0.9205 | 1 | 567 | 10.11056 | 0.05099 | 0 | 615 | 5035.000 | 12.214498 | 0.3295 | 0 | 16 | 1746.0000 | 0.9163803 | 0.01566 | 0 | 0 | 5573 | 0.0000000 | 0.09479 | 0 | 441 | 5608.000 | 7.8637660 | 0.140300 | 0 | 7576 | 3055 | 40.3247096 | 0.9148 | 1 | 72 | 0.9503696 | 0.5383 | 0 | 0 | 2543 | 0.0000000 | 0.09796 | 0 | 125 | 2543.000 | 4.915454 | 0.4934 | 0 | 6 | 5608 | 0.1069900 | 0.4054 | 0 | 2.30022 | 0.4418 | 1 | 1.41144 | 0.04295 | 1 | 0.140300 | 0.139100 | 0 | 2.44986 | 0.4589 | 1 | 6.301820 | 0.2416 | 3 | Yes | 0 | 0 | $0 | 0 | 0 | $0 | 0 | Census Tract 114.07, Baldwin County, Alabama | 22317 | 292600 | 28418 | 241100 | 25887.72 | 339416 | 2530.28 | 0.0977406 | -98316 | -0.2896622 | NA | NA | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
| 01003011502 | 01003 | 011502 | AL | Alabama | Baldwin County | 3 | South Region | 6 | East South Central Division | 9234 | 4606 | 3702 | 3160 | 9213 | 34.29936 | 0.7632 | 1 | 282 | 4002 | 7.046477 | 0.47570 | 0 | 526 | 2158 | 24.37442 | 0.31260 | 0 | 582 | 1544 | 37.69430 | 0.33410 | 0 | 1108 | 3702 | 29.92977 | 0.33740 | 0 | 997 | 6176 | 16.143135 | 0.6201 | 0 | 2074 | 10111 | 20.51231 | 0.7670 | 1 | 1450 | 15.70284 | 0.7043 | 0 | 2491 | 26.97639 | 0.6984 | 0 | 1542 | 7577 | 20.35106 | 0.7842 | 1 | 684 | 2718 | 25.165563 | 0.7767 | 1 | 532 | 8697 | 6.1170519 | 0.78590 | 1 | 3275 | 9234 | 35.466753 | 0.60970 | 0 | 4606 | 214 | 4.6461138 | 0.5268 | 0 | 828 | 17.9765523 | 0.8689 | 1 | 89 | 3702 | 2.404106 | 0.6192 | 0 | 293 | 3702 | 7.9146407 | 0.64700 | 0 | 0 | 9234 | 0.0000 | 0.3640 | 0 | 2.96340 | 0.6387 | 2 | 3.74950 | 0.9623 | 3 | 0.60970 | 0.6040 | 0 | 3.02590 | 0.7475 | 1 | 10.34850 | 0.8024 | 6 | 14165 | 6867 | 6002 | 2853 | 14165 | 20.141193 | 0.5175 | 0 | 313 | 7047 | 4.441606 | 0.46620 | 0 | 1181 | 4164 | 28.362152 | 0.74500 | 0 | 887 | 1838 | 48.25898 | 0.6211 | 0 | 2068 | 6002 | 34.45518 | 0.65900 | 0 | 1667 | 10750 | 15.506977 | 0.7286 | 0 | 2527 | 14165 | 17.839746 | 0.8980 | 1 | 3082 | 21.757854 | 0.7907 | 1 | 2506 | 17.69149 | 0.24240 | 0 | 3004 | 11659.000 | 25.765503 | 0.9038 | 1 | 407 | 3482.0000 | 11.6886847 | 0.39940 | 0 | 364 | 13519 | 2.6925068 | 0.65290 | 0 | 2755 | 14165.000 | 19.4493470 | 0.346300 | 0 | 6867 | 441 | 6.4220183 | 0.5555 | 0 | 526 | 7.6598223 | 0.7585 | 1 | 93 | 6002 | 1.5494835 | 0.46540 | 0 | 184 | 6002.000 | 3.065645 | 0.3373 | 0 | 0 | 14165 | 0.0000000 | 0.1831 | 0 | 3.26930 | 0.7261 | 1 | 2.98920 | 0.76250 | 2 | 0.346300 | 0.343400 | 0 | 2.29980 | 0.3856 | 1 | 8.904600 | 0.6398 | 4 | Yes | 0 | 0 | $0 | 2 | 8860000 | $8,860,000 | 1 | Census Tract 115.02, Baldwin County, Alabama | 20411 | 162700 | 22820 | 180400 | 23676.76 | 188732 | -856.76 | -0.0361857 | -8332 | -0.0441473 | NA | NA | Baldwin County, Alabama | Mobile-Daphne-Fairhope, AL CSA | CS380 |
LIHTC Data
Divisional
svi_divisional_lihtc_df0 <- left_join(svi_divisional_lihtc, census_pull_df, join_by("GEOID_2010_trt" == "GEOID"))
svi_divisional_lihtc_df1 <- left_join(svi_divisional_lihtc_df0, hpi_df_10_20, join_by("GEOID_2010_trt" == "GEOID10")) %>%
unite("county_fips", FIPS_st, FIPS_county, sep = "")
svi_divisional_lihtc_df <- left_join(svi_divisional_lihtc_df1, msa_csa_crosswalk, join_by("county_fips" == "county_fips"))
svi_divisional_lihtc_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | county_fips | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | pre10_lihtc_project_cnt | pre10_lihtc_project_dollars | post10_lihtc_project_cnt | post10_lihtc_project_dollars | lihtc_flag | lihtc_eligibility | NAME | Median_Income_10 | Median_Home_Value_10 | Median_Income_19 | Median_Home_Value_19 | Median_Income_10adj | Median_Home_Value_10adj | Median_Income_Change | Median_Income_Change_pct | Median_Home_Value_Change | Median_Home_Value_Change_pct | housing_price_index10 | housing_price_index20 | county_title | cbsa | cbsa_code |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 04001942600 | 04001 | 942600 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 1561 | 762 | 384 | 1150 | 1561 | 73.67072 | 0.9944 | 1 | 26 | 300 | 8.666667 | 0.6866 | 0 | 65 | 366 | 17.759563 | 0.10180 | 0 | 5 | 18 | 27.77778 | 0.19090 | 0 | 70 | 384 | 18.22917 | 0.05781 | 0 | 303 | 839 | 36.11442 | 0.9335 | 1 | 282 | 1578 | 17.87072 | 0.5921 | 0 | 153 | 9.801409 | 0.449600 | 0 | 560 | 35.874440 | 0.90440 | 1 | 240 | 1054 | 22.770398 | 0.90060 | 1 | 107 | 332 | 32.22892 | 0.9163 | 1 | 168 | 1431 | 11.7400419 | 0.8831 | 1 | 1561 | 1561 | 100.00000 | 0.9989 | 1 | 762 | 0 | 0.0000000 | 0.1526 | 0 | 215 | 28.21522 | 0.9088 | 1 | 117 | 384 | 30.468750 | 0.9979 | 1 | 33 | 384 | 8.593750 | 0.7842 | 1 | 0 | 1561 | 0.000000 | 0.3955 | 0 | 3.26441 | 0.7248 | 2 | 4.054000 | 0.98530 | 4 | 0.9989 | 0.9931 | 1 | 3.2390 | 0.8004 | 3 | 11.556310 | 0.8966 | 10 | 1711 | 676 | 469 | 930 | 1711 | 54.35418 | 0.9708 | 1 | 44 | 484 | 9.090909 | 0.8539 | 1 | 32 | 456 | 7.017544 | 0.02013 | 0 | 4 | 13 | 30.76923 | 0.24630 | 0 | 36 | 469 | 7.675906 | 0.005758 | 0 | 304 | 1197 | 25.396825 | 0.9056 | 1 | 686 | 1711 | 40.093513 | 0.9973 | 1 | 229 | 13.3839860 | 0.439700 | 0 | 347 | 20.280538 | 0.37880 | 0 | 245 | 1363.979 | 17.962156 | 0.6824 | 0 | 49 | 304.0000 | 16.118421 | 0.5859 | 0 | 155 | 1652 | 9.3825666 | 0.8951 | 1 | 1711 | 1710.980 | 100.00115 | 1.0000 | 1 | 676 | 0 | 0.0000000 | 0.1276 | 0 | 142 | 21.0059172 | 0.8736 | 1 | 83 | 469 | 17.697228 | 0.9774 | 1 | 99 | 469.0000 | 21.108742 | 0.96550 | 1 | 0 | 1711 | 0.0000000 | 0.2155 | 0 | 3.733358 | 0.8474 | 4 | 2.981900 | 0.73750 | 1 | 1.0000 | 0.9958 | 1 | 3.15960 | 0.7653 | 3 | 10.87486 | 0.8573 | 9 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9426, Apache County, Arizona | 10268 | 27600 | 15822 | 45700 | 11910.88 | 32016 | 3911.12 | 0.3283653 | 13684 | 0.4274113 | NA | NA | NA | NA | NA |
| 04001942700 | 04001 | 942700 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4886 | 2757 | 1291 | 2616 | 4871 | 53.70560 | 0.9480 | 1 | 163 | 1398 | 11.659514 | 0.8577 | 1 | 102 | 1113 | 9.164421 | 0.01757 | 0 | 54 | 178 | 30.33708 | 0.22790 | 0 | 156 | 1291 | 12.08366 | 0.01652 | 0 | 1039 | 2931 | 35.44865 | 0.9303 | 1 | 1873 | 5249 | 35.68299 | 0.9436 | 1 | 688 | 14.081048 | 0.687000 | 0 | 1530 | 31.313958 | 0.77180 | 1 | 772 | 3514 | 21.969266 | 0.88390 | 1 | 246 | 939 | 26.19808 | 0.8308 | 1 | 592 | 4631 | 12.7834161 | 0.8975 | 1 | 4846 | 4886 | 99.18133 | 0.9946 | 1 | 2757 | 0 | 0.0000000 | 0.1526 | 0 | 369 | 13.38411 | 0.7652 | 1 | 240 | 1291 | 18.590240 | 0.9756 | 1 | 188 | 1291 | 14.562355 | 0.9015 | 1 | 0 | 4886 | 0.000000 | 0.3955 | 0 | 3.69612 | 0.8288 | 4 | 4.071000 | 0.98700 | 4 | 0.9946 | 0.9890 | 1 | 3.1904 | 0.7848 | 3 | 11.952120 | 0.9295 | 12 | 5469 | 2222 | 1462 | 2784 | 5469 | 50.90510 | 0.9557 | 1 | 358 | 1642 | 21.802680 | 0.9925 | 1 | 114 | 1151 | 9.904431 | 0.04797 | 0 | 58 | 311 | 18.64952 | 0.09477 | 0 | 172 | 1462 | 11.764706 | 0.023990 | 0 | 852 | 3274 | 26.023213 | 0.9120 | 1 | 1856 | 5466 | 33.955360 | 0.9919 | 1 | 759 | 13.8782227 | 0.465700 | 0 | 1555 | 28.432986 | 0.77390 | 1 | 706 | 3911.002 | 18.051640 | 0.6872 | 0 | 257 | 1035.0004 | 24.830908 | 0.8039 | 1 | 396 | 5078 | 7.7983458 | 0.8624 | 1 | 5420 | 5469.002 | 99.10401 | 0.9946 | 1 | 2222 | 0 | 0.0000000 | 0.1276 | 0 | 400 | 18.0018002 | 0.8488 | 1 | 238 | 1462 | 16.279070 | 0.9710 | 1 | 175 | 1462.0007 | 11.969898 | 0.87420 | 1 | 26 | 5469 | 0.4754068 | 0.6430 | 0 | 3.876090 | 0.8796 | 4 | 3.593100 | 0.94210 | 3 | 0.9946 | 0.9905 | 1 | 3.46460 | 0.8721 | 3 | 11.92839 | 0.9425 | 11 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9427, Apache County, Arizona | 14348 | 55900 | 18740 | 47200 | 16643.68 | 64844 | 2096.32 | 0.1259529 | -17644 | -0.2720992 | NA | NA | NA | NA | NA |
| 04001944100 | 04001 | 944100 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 4975 | 2485 | 1204 | 3251 | 4968 | 65.43881 | 0.9846 | 1 | 210 | 1254 | 16.746412 | 0.9576 | 1 | 122 | 905 | 13.480663 | 0.04383 | 0 | 91 | 299 | 30.43478 | 0.22960 | 0 | 213 | 1204 | 17.69103 | 0.05320 | 0 | 779 | 2325 | 33.50538 | 0.9203 | 1 | 1293 | 5511 | 23.46217 | 0.7705 | 1 | 344 | 6.914573 | 0.270100 | 0 | 1993 | 40.060302 | 0.97010 | 1 | 577 | 3087 | 18.691286 | 0.77990 | 1 | 278 | 893 | 31.13102 | 0.9038 | 1 | 308 | 4470 | 6.8903803 | 0.7895 | 1 | 4915 | 4975 | 98.79397 | 0.9929 | 1 | 2485 | 21 | 0.8450704 | 0.3700 | 0 | 428 | 17.22334 | 0.8203 | 1 | 257 | 1204 | 21.345515 | 0.9843 | 1 | 212 | 1204 | 17.607973 | 0.9391 | 1 | 0 | 4975 | 0.000000 | 0.3955 | 0 | 3.68620 | 0.8261 | 4 | 3.713400 | 0.95280 | 4 | 0.9929 | 0.9872 | 1 | 3.5092 | 0.8926 | 3 | 11.901700 | 0.9244 | 12 | 6183 | 2379 | 1424 | 3704 | 5789 | 63.98342 | 0.9912 | 1 | 425 | 1608 | 26.430348 | 0.9954 | 1 | 132 | 1163 | 11.349957 | 0.07802 | 0 | 38 | 261 | 14.55939 | 0.06498 | 0 | 170 | 1424 | 11.938202 | 0.026300 | 0 | 862 | 3259 | 26.449831 | 0.9148 | 1 | 1320 | 6183 | 21.348860 | 0.9283 | 1 | 637 | 10.3024422 | 0.271800 | 0 | 1869 | 30.228045 | 0.83960 | 1 | 626 | 3964.000 | 15.792129 | 0.5715 | 0 | 371 | 991.0000 | 37.436932 | 0.9557 | 1 | 315 | 5717 | 5.5098828 | 0.8021 | 1 | 5981 | 6182.998 | 96.73300 | 0.9841 | 1 | 2379 | 0 | 0.0000000 | 0.1276 | 0 | 442 | 18.5792350 | 0.8550 | 1 | 379 | 1424 | 26.615168 | 0.9969 | 1 | 347 | 1424.0000 | 24.367977 | 0.97580 | 1 | 394 | 6183 | 6.3723112 | 0.9380 | 1 | 3.856000 | 0.8749 | 4 | 3.440700 | 0.90700 | 3 | 0.9841 | 0.9800 | 1 | 3.89330 | 0.9609 | 4 | 12.17410 | 0.9549 | 12 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9441, Apache County, Arizona | 13469 | 60900 | 16162 | 46800 | 15624.04 | 70644 | 537.96 | 0.0344316 | -23844 | -0.3375234 | NA | NA | NA | NA | NA |
| 04001944300 | 04001 | 944300 | AZ | Arizona | Apache County | 4 | West Region | 8 | Mountain Division | 6806 | 3308 | 1826 | 4099 | 6797 | 60.30602 | 0.9762 | 1 | 403 | 1777 | 22.678672 | 0.9858 | 1 | 154 | 1457 | 10.569664 | 0.02549 | 0 | 63 | 369 | 17.07317 | 0.08684 | 0 | 217 | 1826 | 11.88390 | 0.01536 | 0 | 1432 | 3367 | 42.53044 | 0.9623 | 1 | 2305 | 7092 | 32.50141 | 0.9160 | 1 | 746 | 10.960917 | 0.517600 | 0 | 2767 | 40.655304 | 0.97610 | 1 | 842 | 4361 | 19.307498 | 0.80410 | 1 | 357 | 1163 | 30.69647 | 0.8982 | 1 | 568 | 6178 | 9.1939139 | 0.8423 | 1 | 6750 | 6806 | 99.17720 | 0.9944 | 1 | 3308 | 8 | 0.2418380 | 0.3113 | 0 | 440 | 13.30109 | 0.7638 | 1 | 404 | 1826 | 22.124863 | 0.9856 | 1 | 388 | 1826 | 21.248631 | 0.9627 | 1 | 139 | 6806 | 2.042316 | 0.8458 | 1 | 3.85566 | 0.8602 | 4 | 4.038300 | 0.98440 | 4 | 0.9944 | 0.9888 | 1 | 3.8692 | 0.9619 | 4 | 12.757560 | 0.9749 | 13 | 5922 | 2801 | 2026 | 3548 | 5916 | 59.97295 | 0.9854 | 1 | 67 | 1402 | 4.778887 | 0.5316 | 0 | 251 | 1664 | 15.084135 | 0.20570 | 0 | 46 | 362 | 12.70718 | 0.05498 | 0 | 297 | 2026 | 14.659427 | 0.056430 | 0 | 844 | 3696 | 22.835498 | 0.8792 | 1 | 2528 | 5916 | 42.731575 | 0.9987 | 1 | 793 | 13.3907464 | 0.440100 | 0 | 1663 | 28.081729 | 0.75750 | 1 | 573 | 4258.743 | 13.454674 | 0.4253 | 0 | 301 | 1112.2581 | 27.062064 | 0.8474 | 1 | 851 | 5568 | 15.2837644 | 0.9575 | 1 | 5880 | 5922.449 | 99.28326 | 0.9964 | 1 | 2801 | 22 | 0.7854338 | 0.3369 | 0 | 521 | 18.6004998 | 0.8557 | 1 | 267 | 2026 | 13.178677 | 0.9482 | 1 | 297 | 2025.6898 | 14.661672 | 0.91580 | 1 | 11 | 5922 | 0.1857481 | 0.5222 | 0 | 3.451330 | 0.7773 | 3 | 3.427800 | 0.90080 | 3 | 0.9964 | 0.9922 | 1 | 3.57880 | 0.9040 | 3 | 11.45433 | 0.9088 | 10 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9443, Apache County, Arizona | 11133 | 48700 | 15051 | 53700 | 12914.28 | 56492 | 2136.72 | 0.1654541 | -2792 | -0.0494229 | NA | NA | NA | NA | NA |
| 04005000800 | 04005 | 000800 | AZ | Arizona | Coconino County | 4 | West Region | 8 | Mountain Division | 3912 | 1200 | 1057 | 1511 | 2859 | 52.85065 | 0.9430 | 1 | 54 | 1952 | 2.766393 | 0.1150 | 0 | 71 | 192 | 36.979167 | 0.73370 | 0 | 509 | 865 | 58.84393 | 0.83080 | 1 | 580 | 1057 | 54.87228 | 0.96160 | 1 | 265 | 1897 | 13.96943 | 0.6489 | 0 | 995 | 3589 | 27.72360 | 0.8536 | 1 | 121 | 3.093047 | 0.062070 | 0 | 208 | 5.316973 | 0.02835 | 0 | 248 | 3170 | 7.823344 | 0.15510 | 0 | 53 | 311 | 17.04180 | 0.5919 | 0 | 26 | 3898 | 0.6670087 | 0.3063 | 0 | 1410 | 3912 | 36.04294 | 0.6285 | 0 | 1200 | 155 | 12.9166667 | 0.7329 | 0 | 3 | 0.25000 | 0.3706 | 0 | 31 | 1057 | 2.932829 | 0.6261 | 0 | 33 | 1057 | 3.122044 | 0.4682 | 0 | 1043 | 3912 | 26.661554 | 0.9826 | 1 | 3.52210 | 0.7887 | 3 | 1.143720 | 0.02019 | 0 | 0.6285 | 0.6250 | 0 | 3.1804 | 0.7810 | 1 | 8.474720 | 0.5850 | 4 | 6428 | 2343 | 2163 | 3238 | 5850 | 55.35043 | 0.9741 | 1 | 399 | 3753 | 10.631495 | 0.9047 | 1 | 43 | 312 | 13.782051 | 0.15050 | 0 | 1188 | 1850 | 64.21622 | 0.93540 | 1 | 1231 | 2162 | 56.938020 | 0.988900 | 1 | 364 | 2823 | 12.894084 | 0.7116 | 0 | 478 | 5900 | 8.101695 | 0.4937 | 0 | 262 | 4.0759179 | 0.030250 | 0 | 634 | 9.863099 | 0.06202 | 0 | 497 | 5227.333 | 9.507716 | 0.1782 | 0 | 112 | 544.6422 | 20.563958 | 0.7139 | 0 | 56 | 6207 | 0.9022072 | 0.4074 | 0 | 2862 | 6428.175 | 44.52274 | 0.6490 | 0 | 2343 | 838 | 35.7661118 | 0.9165 | 1 | 11 | 0.4694836 | 0.4053 | 0 | 116 | 2163 | 5.362922 | 0.7808 | 1 | 166 | 2162.6681 | 7.675704 | 0.76580 | 1 | 759 | 6428 | 11.8077162 | 0.9625 | 1 | 4.073000 | 0.9190 | 3 | 1.391770 | 0.04857 | 0 | 0.6490 | 0.6463 | 0 | 3.83090 | 0.9524 | 4 | 9.94467 | 0.7611 | 7 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 8, Coconino County, Arizona | 8201 | 236500 | 14117 | 292500 | 9513.16 | 274340 | 4603.84 | 0.4839443 | 18160 | 0.0661952 | 151.60 | 249.17 | Coconino County, Arizona | Flagstaff, AZ MSA | C2238 |
| 04005001000 | 04005 | 001000 | AZ | Arizona | Coconino County | 4 | West Region | 8 | Mountain Division | 7519 | 863 | 763 | 1197 | 1744 | 68.63532 | 0.9894 | 1 | 1067 | 4202 | 25.392670 | 0.9925 | 1 | 17 | 25 | 68.000000 | 0.99610 | 1 | 484 | 738 | 65.58266 | 0.91810 | 1 | 501 | 763 | 65.66186 | 0.99650 | 1 | 47 | 886 | 5.30474 | 0.2676 | 0 | 1429 | 8331 | 17.15280 | 0.5641 | 0 | 0 | 0.000000 | 0.003736 | 0 | 310 | 4.122889 | 0.02165 | 0 | 54 | 1560 | 3.461539 | 0.01727 | 0 | 23 | 174 | 13.21839 | 0.4495 | 0 | 233 | 7411 | 3.1439752 | 0.6314 | 0 | 2495 | 7519 | 33.18260 | 0.5941 | 0 | 863 | 441 | 51.1008111 | 0.9666 | 1 | 35 | 4.05562 | 0.6079 | 0 | 14 | 763 | 1.834862 | 0.4856 | 0 | 119 | 763 | 15.596330 | 0.9127 | 1 | 5775 | 7519 | 76.805426 | 0.9946 | 1 | 3.81010 | 0.8520 | 3 | 1.123556 | 0.01848 | 0 | 0.5941 | 0.5907 | 0 | 3.9674 | 0.9733 | 3 | 9.495156 | 0.7036 | 6 | 13499 | 815 | 675 | 1056 | 1313 | 80.42650 | 0.9987 | 1 | 1353 | 6344 | 21.327238 | 0.9918 | 1 | 22 | 35 | 62.857143 | 0.99810 | 1 | 500 | 641 | 78.00312 | 0.99310 | 1 | 522 | 676 | 77.218935 | 0.999600 | 1 | 29 | 460 | 6.304348 | 0.4346 | 0 | 1051 | 13483 | 7.795001 | 0.4716 | 0 | 17 | 0.1259353 | 0.004211 | 0 | 221 | 1.637158 | 0.01474 | 0 | 125 | 1282.667 | 9.745322 | 0.1874 | 0 | 42 | 114.3578 | 36.726848 | 0.9505 | 1 | 207 | 13491 | 1.5343562 | 0.5203 | 0 | 4803 | 13498.825 | 35.58088 | 0.5539 | 0 | 815 | 550 | 67.4846626 | 0.9864 | 1 | 7 | 0.8588957 | 0.4653 | 0 | 62 | 675 | 9.185185 | 0.8933 | 1 | 134 | 675.3319 | 19.842095 | 0.96070 | 1 | 12185 | 13499 | 90.2659456 | 0.9960 | 1 | 3.896300 | 0.8850 | 3 | 1.677151 | 0.11070 | 1 | 0.5539 | 0.5516 | 0 | 4.30170 | 0.9882 | 4 | 10.42905 | 0.8107 | 8 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 10, Coconino County, Arizona | 4710 | 118400 | 4039 | NA | 5463.60 | 137344 | -1424.60 | -0.2607438 | NA | NA | NA | NA | Coconino County, Arizona | Flagstaff, AZ MSA | C2238 |
| 04007940200 | 04007 | 940200 | AZ | Arizona | Gila County | 4 | West Region | 8 | Mountain Division | 760 | 380 | 198 | 599 | 760 | 78.81579 | 0.9971 | 1 | 14 | 202 | 6.930693 | 0.5411 | 0 | 56 | 130 | 43.076923 | 0.87120 | 1 | 12 | 68 | 17.64706 | 0.09167 | 0 | 68 | 198 | 34.34343 | 0.48740 | 0 | 142 | 386 | 36.78756 | 0.9383 | 1 | 494 | 1394 | 35.43759 | 0.9419 | 1 | 39 | 5.131579 | 0.165100 | 0 | 294 | 38.684210 | 0.95480 | 1 | 245 | 807 | 30.359356 | 0.98120 | 1 | 33 | 141 | 23.40426 | 0.7730 | 1 | 36 | 676 | 5.3254438 | 0.7379 | 0 | 760 | 760 | 100.00000 | 0.9989 | 1 | 380 | 0 | 0.0000000 | 0.1526 | 0 | 55 | 14.47368 | 0.7834 | 1 | 12 | 198 | 6.060606 | 0.8228 | 1 | 31 | 198 | 15.656566 | 0.9136 | 1 | 0 | 760 | 0.000000 | 0.3955 | 0 | 3.90580 | 0.8699 | 3 | 3.612000 | 0.93710 | 3 | 0.9989 | 0.9931 | 1 | 3.0679 | 0.7370 | 3 | 11.584600 | 0.8992 | 10 | 2341 | 555 | 478 | 1464 | 2332 | 62.77873 | 0.9891 | 1 | 103 | 582 | 17.697595 | 0.9847 | 1 | 28 | 301 | 9.302326 | 0.03891 | 0 | 31 | 177 | 17.51412 | 0.08439 | 0 | 59 | 478 | 12.343096 | 0.031290 | 0 | 364 | 1073 | 33.923579 | 0.9585 | 1 | 300 | 2341 | 12.815036 | 0.7377 | 0 | 149 | 6.3648014 | 0.087670 | 0 | 1122 | 47.928236 | 0.99900 | 1 | 303 | 1219.000 | 24.856440 | 0.9002 | 1 | 133 | 395.0000 | 33.670886 | 0.9294 | 1 | 27 | 2020 | 1.3366337 | 0.4895 | 0 | 2321 | 2341.000 | 99.14566 | 0.9948 | 1 | 555 | 0 | 0.0000000 | 0.1276 | 0 | 22 | 3.9639640 | 0.6253 | 0 | 137 | 478 | 28.661088 | 0.9977 | 1 | 102 | 478.0000 | 21.338912 | 0.96700 | 1 | 0 | 2341 | 0.0000000 | 0.2155 | 0 | 3.701290 | 0.8371 | 3 | 3.405770 | 0.89580 | 3 | 0.9948 | 0.9907 | 1 | 2.93310 | 0.6760 | 2 | 11.03496 | 0.8720 | 9 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9402, Gila County, Arizona | 20607 | 83800 | 14301 | 55800 | 23904.12 | 97208 | -9603.12 | -0.4017349 | -41408 | -0.4259732 | NA | NA | Gila County, Arizona | Payson, AZ MicroSA | C3774 |
| 04007940400 | 04007 | 940400 | AZ | Arizona | Gila County | 4 | West Region | 8 | Mountain Division | 6485 | 1464 | 1041 | 3673 | 6485 | 56.63840 | 0.9620 | 1 | 277 | 1834 | 15.103599 | 0.9368 | 1 | 101 | 681 | 14.831131 | 0.05870 | 0 | 56 | 360 | 15.55556 | 0.07525 | 0 | 157 | 1041 | 15.08165 | 0.03361 | 0 | 1155 | 3309 | 34.90481 | 0.9266 | 1 | 2644 | 5767 | 45.84706 | 0.9889 | 1 | 408 | 6.291442 | 0.234900 | 0 | 2406 | 37.101002 | 0.93050 | 1 | 692 | 3817 | 18.129421 | 0.76010 | 1 | 354 | 861 | 41.11498 | 0.9756 | 1 | 30 | 5565 | 0.5390836 | 0.2729 | 0 | 6428 | 6485 | 99.12105 | 0.9937 | 1 | 1464 | 0 | 0.0000000 | 0.1526 | 0 | 335 | 22.88251 | 0.8750 | 1 | 248 | 1041 | 23.823247 | 0.9891 | 1 | 202 | 1041 | 19.404419 | 0.9537 | 1 | 0 | 6485 | 0.000000 | 0.3955 | 0 | 3.84791 | 0.8589 | 4 | 3.174000 | 0.80420 | 3 | 0.9937 | 0.9880 | 1 | 3.3659 | 0.8488 | 3 | 11.381510 | 0.8800 | 11 | 5873 | 1751 | 1496 | 3435 | 5862 | 58.59775 | 0.9829 | 1 | 357 | 1977 | 18.057663 | 0.9860 | 1 | 114 | 799 | 14.267835 | 0.17090 | 0 | 114 | 697 | 16.35581 | 0.07632 | 0 | 228 | 1496 | 15.240642 | 0.066600 | 0 | 819 | 3169 | 25.844115 | 0.9099 | 1 | 486 | 5872 | 8.276567 | 0.5054 | 0 | 464 | 7.9005619 | 0.154300 | 0 | 2015 | 34.309552 | 0.94120 | 1 | 697 | 3857.000 | 18.071040 | 0.6887 | 0 | 399 | 1240.0000 | 32.177419 | 0.9121 | 1 | 116 | 5320 | 2.1804511 | 0.6047 | 0 | 5766 | 5873.000 | 98.17810 | 0.9899 | 1 | 1751 | 10 | 0.5711022 | 0.3116 | 0 | 410 | 23.4151913 | 0.8922 | 1 | 290 | 1496 | 19.385027 | 0.9818 | 1 | 322 | 1496.0000 | 21.524064 | 0.96800 | 1 | 4 | 5873 | 0.0681083 | 0.4458 | 0 | 3.450800 | 0.7771 | 3 | 3.301000 | 0.86590 | 2 | 0.9899 | 0.9857 | 1 | 3.59940 | 0.9095 | 3 | 11.34110 | 0.8981 | 9 | 0 | 0 | 1 | 547218 | 1 | Yes | Census Tract 9404, Gila County, Arizona | 14125 | 57900 | 19488 | 40200 | 16385.00 | 67164 | 3103.00 | 0.1893805 | -26964 | -0.4014651 | NA | NA | Gila County, Arizona | Payson, AZ MicroSA | C3774 |
| 04009940500 | 04009 | 940500 | AZ | Arizona | Graham County | 4 | West Region | 8 | Mountain Division | 4838 | 1186 | 1054 | 3261 | 4811 | 67.78217 | 0.9883 | 1 | 392 | 1501 | 26.115923 | 0.9935 | 1 | 118 | 582 | 20.274914 | 0.15470 | 0 | 86 | 472 | 18.22034 | 0.09660 | 0 | 204 | 1054 | 19.35484 | 0.07125 | 0 | 622 | 2290 | 27.16157 | 0.8736 | 1 | 2211 | 4615 | 47.90899 | 0.9927 | 1 | 235 | 4.857379 | 0.147100 | 0 | 2057 | 42.517569 | 0.98700 | 1 | 599 | 2750 | 21.781818 | 0.87800 | 1 | 453 | 874 | 51.83066 | 0.9942 | 1 | 134 | 4253 | 3.1507171 | 0.6320 | 0 | 4838 | 4838 | 100.00000 | 0.9989 | 1 | 1186 | 0 | 0.0000000 | 0.1526 | 0 | 157 | 13.23777 | 0.7625 | 1 | 259 | 1054 | 24.573055 | 0.9906 | 1 | 256 | 1054 | 24.288425 | 0.9752 | 1 | 0 | 4838 | 0.000000 | 0.3955 | 0 | 3.91935 | 0.8730 | 4 | 3.638300 | 0.94100 | 3 | 0.9989 | 0.9931 | 1 | 3.2764 | 0.8163 | 3 | 11.832950 | 0.9185 | 11 | 4698 | 1271 | 1088 | 2479 | 4644 | 53.38071 | 0.9680 | 1 | 320 | 1512 | 21.164021 | 0.9916 | 1 | 49 | 635 | 7.716535 | 0.02543 | 0 | 59 | 453 | 13.02428 | 0.05556 | 0 | 108 | 1088 | 9.926471 | 0.011900 | 0 | 524 | 2457 | 21.326821 | 0.8647 | 1 | 748 | 4698 | 15.921669 | 0.8382 | 1 | 411 | 8.7484036 | 0.196800 | 0 | 1750 | 37.249894 | 0.97360 | 1 | 483 | 2948.001 | 16.383982 | 0.6023 | 0 | 243 | 867.0002 | 28.027676 | 0.8613 | 1 | 28 | 4096 | 0.6835938 | 0.3526 | 0 | 4691 | 4698.001 | 99.85097 | 0.9987 | 1 | 1271 | 0 | 0.0000000 | 0.1276 | 0 | 132 | 10.3855232 | 0.7441 | 0 | 187 | 1088 | 17.187500 | 0.9751 | 1 | 190 | 1088.0003 | 17.463231 | 0.94690 | 1 | 8 | 4698 | 0.1702852 | 0.5117 | 0 | 3.674400 | 0.8291 | 4 | 2.986600 | 0.73960 | 2 | 0.9987 | 0.9945 | 1 | 3.30540 | 0.8183 | 2 | 10.96510 | 0.8644 | 9 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9405, Graham County, Arizona | 12156 | 52100 | 17406 | 30200 | 14100.96 | 60436 | 3305.04 | 0.2343840 | -30236 | -0.5002978 | NA | NA | Graham County, Arizona | Safford, AZ MicroSA | C4094 |
| 04013050603 | 04013 | 050603 | AZ | Arizona | Maricopa County | 4 | West Region | 8 | Mountain Division | 3210 | 1306 | 1019 | 935 | 3203 | 29.19138 | 0.6976 | 0 | 123 | 1440 | 8.541667 | 0.6788 | 0 | 173 | 827 | 20.918984 | 0.17220 | 0 | 80 | 192 | 41.66667 | 0.44980 | 0 | 253 | 1019 | 24.82826 | 0.17710 | 0 | 478 | 1973 | 24.22707 | 0.8412 | 1 | 973 | 3641 | 26.72343 | 0.8371 | 1 | 284 | 8.847352 | 0.386600 | 0 | 996 | 31.028037 | 0.76090 | 1 | 303 | 2615 | 11.586998 | 0.38900 | 0 | 88 | 810 | 10.86420 | 0.3488 | 0 | 138 | 3010 | 4.5847176 | 0.7109 | 0 | 1310 | 3210 | 40.80997 | 0.6759 | 0 | 1306 | 0 | 0.0000000 | 0.1526 | 0 | 720 | 55.13017 | 0.9795 | 1 | 69 | 1019 | 6.771344 | 0.8464 | 1 | 39 | 1019 | 3.827282 | 0.5281 | 0 | 0 | 3210 | 0.000000 | 0.3955 | 0 | 3.23180 | 0.7166 | 2 | 2.596200 | 0.55280 | 1 | 0.6759 | 0.6720 | 0 | 2.9021 | 0.6670 | 2 | 9.406000 | 0.6968 | 5 | 6148 | 2245 | 1921 | 1186 | 6098 | 19.44900 | 0.5140 | 0 | 378 | 2678 | 14.115011 | 0.9622 | 1 | 277 | 1535 | 18.045603 | 0.35540 | 0 | 43 | 387 | 11.11111 | 0.04642 | 0 | 320 | 1922 | 16.649324 | 0.093090 | 0 | 1099 | 4207 | 26.123128 | 0.9131 | 1 | 1084 | 6144 | 17.643229 | 0.8762 | 1 | 814 | 13.2400781 | 0.433200 | 0 | 1313 | 21.356539 | 0.43200 | 0 | 1259 | 4836.918 | 26.028972 | 0.9197 | 1 | 72 | 1493.4212 | 4.821145 | 0.1184 | 0 | 372 | 5967 | 6.2342886 | 0.8243 | 1 | 2088 | 6148.289 | 33.96067 | 0.5342 | 0 | 2245 | 0 | 0.0000000 | 0.1276 | 0 | 1081 | 48.1514477 | 0.9699 | 1 | 65 | 1921 | 3.383654 | 0.6475 | 0 | 0 | 1921.1833 | 0.000000 | 0.03808 | 0 | 7 | 6148 | 0.1138582 | 0.4734 | 0 | 3.358590 | 0.7560 | 3 | 2.727600 | 0.61500 | 2 | 0.5342 | 0.5320 | 0 | 2.25648 | 0.3825 | 1 | 8.87687 | 0.6322 | 6 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 506.03, Maricopa County, Arizona | 26439 | 156000 | 23698 | 165600 | 30669.24 | 180960 | -6971.24 | -0.2273040 | -15360 | -0.0848806 | 83.88 | 195.56 | Maricopa County, Arizona | Phoenix-Mesa-Scottsdale, AZ MSA | C3806 |
National
svi_national_lihtc_df0 <- left_join(svi_national_lihtc, census_pull_df, join_by("GEOID_2010_trt" == "GEOID"))
svi_national_lihtc_df1 <- left_join(svi_national_lihtc_df0, hpi_df_10_20, join_by("GEOID_2010_trt" == "GEOID10")) %>%
unite("county_fips", FIPS_st, FIPS_county, sep = "")
svi_national_lihtc_df <- left_join(svi_national_lihtc_df1, msa_csa_crosswalk, join_by("county_fips" == "county_fips"))
svi_national_lihtc_df %>% head(10) %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | county_fips | FIPS_tract | state | state_name | county | region_number | region | division_number | division | E_TOTPOP_10 | E_HU_10 | E_HH_10 | E_POV150_10 | ET_POVSTATUS_10 | EP_POV150_10 | EPL_POV150_10 | F_POV150_10 | E_UNEMP_10 | ET_EMPSTATUS_10 | EP_UNEMP_10 | EPL_UNEMP_10 | F_UNEMP_10 | E_HBURD_OWN_10 | ET_HOUSINGCOST_OWN_10 | EP_HBURD_OWN_10 | EPL_HBURD_OWN_10 | F_HBURD_OWN_10 | E_HBURD_RENT_10 | ET_HOUSINGCOST_RENT_10 | EP_HBURD_RENT_10 | EPL_HBURD_RENT_10 | F_HBURD_RENT_10 | E_HBURD_10 | ET_HOUSINGCOST_10 | EP_HBURD_10 | EPL_HBURD_10 | F_HBURD_10 | E_NOHSDP_10 | ET_EDSTATUS_10 | EP_NOHSDP_10 | EPL_NOHSDP_10 | F_NOHSDP_10 | E_UNINSUR_12 | ET_INSURSTATUS_12 | EP_UNINSUR_12 | EPL_UNINSUR_12 | F_UNINSUR_12 | E_AGE65_10 | EP_AGE65_10 | EPL_AGE65_10 | F_AGE65_10 | E_AGE17_10 | EP_AGE17_10 | EPL_AGE17_10 | F_AGE17_10 | E_DISABL_12 | ET_DISABLSTATUS_12 | EP_DISABL_12 | EPL_DISABL_12 | F_DISABL_12 | E_SNGPNT_10 | ET_FAMILIES_10 | EP_SNGPNT_10 | EPL_SNGPNT_10 | F_SNGPNT_10 | E_LIMENG_10 | ET_POPAGE5UP_10 | EP_LIMENG_10 | EPL_LIMENG_10 | F_LIMENG_10 | E_MINRTY_10 | ET_POPETHRACE_10 | EP_MINRTY_10 | EPL_MINRTY_10 | F_MINRTY_10 | E_STRHU_10 | E_MUNIT_10 | EP_MUNIT_10 | EPL_MUNIT_10 | F_MUNIT_10 | E_MOBILE_10 | EP_MOBILE_10 | EPL_MOBILE_10 | F_MOBILE_10 | E_CROWD_10 | ET_OCCUPANTS_10 | EP_CROWD_10 | EPL_CROWD_10 | F_CROWD_10 | E_NOVEH_10 | ET_KNOWNVEH_10 | EP_NOVEH_10 | EPL_NOVEH_10 | F_NOVEH_10 | E_GROUPQ_10 | ET_HHTYPE_10 | EP_GROUPQ_10 | EPL_GROUPQ_10 | F_GROUPQ_10 | SPL_THEME1_10 | RPL_THEME1_10 | F_THEME1_10 | SPL_THEME2_10 | RPL_THEME2_10 | F_THEME2_10 | SPL_THEME3_10 | RPL_THEME3_10 | F_THEME3_10 | SPL_THEME4_10 | RPL_THEME4_10 | F_THEME4_10 | SPL_THEMES_10 | RPL_THEMES_10 | F_TOTAL_10 | E_TOTPOP_20 | E_HU_20 | E_HH_20 | E_POV150_20 | ET_POVSTATUS_20 | EP_POV150_20 | EPL_POV150_20 | F_POV150_20 | E_UNEMP_20 | ET_EMPSTATUS_20 | EP_UNEMP_20 | EPL_UNEMP_20 | F_UNEMP_20 | E_HBURD_OWN_20 | ET_HOUSINGCOST_OWN_20 | EP_HBURD_OWN_20 | EPL_HBURD_OWN_20 | F_HBURD_OWN_20 | E_HBURD_RENT_20 | ET_HOUSINGCOST_RENT_20 | EP_HBURD_RENT_20 | EPL_HBURD_RENT_20 | F_HBURD_RENT_20 | E_HBURD_20 | ET_HOUSINGCOST_20 | EP_HBURD_20 | EPL_HBURD_20 | F_HBURD_20 | E_NOHSDP_20 | ET_EDSTATUS_20 | EP_NOHSDP_20 | EPL_NOHSDP_20 | F_NOHSDP_20 | E_UNINSUR_20 | ET_INSURSTATUS_20 | EP_UNINSUR_20 | EPL_UNINSUR_20 | F_UNINSUR_20 | E_AGE65_20 | EP_AGE65_20 | EPL_AGE65_20 | F_AGE65_20 | E_AGE17_20 | EP_AGE17_20 | EPL_AGE17_20 | F_AGE17_20 | E_DISABL_20 | ET_DISABLSTATUS_20 | EP_DISABL_20 | EPL_DISABL_20 | F_DISABL_20 | E_SNGPNT_20 | ET_FAMILIES_20 | EP_SNGPNT_20 | EPL_SNGPNT_20 | F_SNGPNT_20 | E_LIMENG_20 | ET_POPAGE5UP_20 | EP_LIMENG_20 | EPL_LIMENG_20 | F_LIMENG_20 | E_MINRTY_20 | ET_POPETHRACE_20 | EP_MINRTY_20 | EPL_MINRTY_20 | F_MINRTY_20 | E_STRHU_20 | E_MUNIT_20 | EP_MUNIT_20 | EPL_MUNIT_20 | F_MUNIT_20 | E_MOBILE_20 | EP_MOBILE_20 | EPL_MOBILE_20 | F_MOBILE_20 | E_CROWD_20 | ET_OCCUPANTS_20 | EP_CROWD_20 | EPL_CROWD_20 | F_CROWD_20 | E_NOVEH_20 | ET_KNOWNVEH_20 | EP_NOVEH_20 | EPL_NOVEH_20 | F_NOVEH_20 | E_GROUPQ_20 | ET_HHTYPE_20 | EP_GROUPQ_20 | EPL_GROUPQ_20 | F_GROUPQ_20 | SPL_THEME1_20 | RPL_THEME1_20 | F_THEME1_20 | SPL_THEME2_20 | RPL_THEME2_20 | F_THEME2_20 | SPL_THEME3_20 | RPL_THEME3_20 | F_THEME3_20 | SPL_THEME4_20 | RPL_THEME4_20 | F_THEME4_20 | SPL_THEMES_20 | RPL_THEMES_20 | F_TOTAL_20 | pre10_lihtc_project_cnt | pre10_lihtc_project_dollars | post10_lihtc_project_cnt | post10_lihtc_project_dollars | lihtc_flag | lihtc_eligibility | NAME | Median_Income_10 | Median_Home_Value_10 | Median_Income_19 | Median_Home_Value_19 | Median_Income_10adj | Median_Home_Value_10adj | Median_Income_Change | Median_Income_Change_pct | Median_Home_Value_Change | Median_Home_Value_Change_pct | housing_price_index10 | housing_price_index20 | county_title | cbsa | cbsa_code |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 01005950700 | 01005 | 950700 | AL | Alabama | Barbour County | 3 | South Region | 6 | East South Central Division | 1753 | 687 | 563 | 615 | 1628 | 37.77641 | 0.8088 | 1 | 17 | 667 | 2.548726 | 0.06941 | 0 | 41 | 376 | 10.90426 | 0.01945 | 0 | 62 | 187 | 33.15508 | 0.24640 | 0 | 103 | 563 | 18.29485 | 0.04875 | 0 | 264 | 1208 | 21.85430 | 0.7570 | 1 | 201 | 1527 | 13.163065 | 0.4991 | 0 | 368 | 20.992584 | 0.89510 | 1 | 462 | 26.354820 | 0.66130 | 0 | 211 | 1085 | 19.44700 | 0.7505 | 1 | 107 | 399 | 26.81704 | 0.8048 | 1 | 0 | 1628 | 0.0000000 | 0.09298 | 0 | 861 | 1753 | 49.11580 | 0.7101 | 0 | 687 | 17 | 2.4745269 | 0.4324 | 0 | 38 | 5.5312955 | 0.6970 | 0 | 3 | 563 | 0.5328597 | 0.3037 | 0 | 19 | 563 | 3.374778 | 0.3529 | 0 | 233 | 1753 | 13.29150 | 0.9517 | 1 | 2.18306 | 0.4137 | 2 | 3.20468 | 0.8377 | 3 | 0.7101 | 0.7035 | 0 | 2.7377 | 0.6100 | 1 | 8.83554 | 0.6264 | 6 | 1527 | 691 | 595 | 565 | 1365 | 41.39194 | 0.8765 | 1 | 37 | 572 | 6.468532 | 0.6776 | 0 | 70 | 376 | 18.617021 | 0.38590 | 0 | 92 | 219 | 42.009132 | 0.47360 | 0 | 162 | 595 | 27.22689 | 0.44540 | 0 | 280 | 1114 | 25.13465 | 0.8942 | 1 | 105 | 1378 | 7.619739 | 0.5505 | 0 | 383 | 25.081860 | 0.88450 | 1 | 337 | 22.069417 | 0.51380 | 0 | 237 | 1041.0000 | 22.76657 | 0.8360 | 1 | 144 | 413.0000 | 34.86683 | 0.9114 | 1 | 11 | 1466 | 0.7503411 | 0.40700 | 0 | 711 | 1527.0000 | 46.56189 | 0.6441 | 0 | 691 | 13 | 1.8813314 | 0.3740 | 0 | 37 | 5.3545586 | 0.7152 | 0 | 0 | 595 | 0.0000000 | 0.09796 | 0 | 115 | 595.0000 | 19.327731 | 0.8859 | 1 | 149 | 1527 | 9.7576948 | 0.9470 | 1 | 3.44420 | 0.7707 | 2 | 3.55270 | 0.9403 | 3 | 0.6441 | 0.6387 | 0 | 3.02006 | 0.7337 | 2 | 10.66106 | 0.8537 | 7 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9507, Barbour County, Alabama | 15257 | 133700 | 17244 | 137500 | 17698.12 | 155092 | -454.12 | -0.0256592 | -17592 | -0.1134294 | 131.05 | 135.61 | Barbour County, Alabama | Eufaula, AL-GA MicroSA | C2164 |
| 01011952100 | 01011 | 952100 | AL | Alabama | Bullock County | 3 | South Region | 6 | East South Central Division | 1652 | 796 | 554 | 564 | 1652 | 34.14044 | 0.7613 | 1 | 46 | 816 | 5.637255 | 0.33630 | 0 | 96 | 458 | 20.96070 | 0.19930 | 0 | 62 | 96 | 64.58333 | 0.89170 | 1 | 158 | 554 | 28.51986 | 0.29220 | 0 | 271 | 1076 | 25.18587 | 0.8163 | 1 | 155 | 1663 | 9.320505 | 0.3183 | 0 | 199 | 12.046005 | 0.47180 | 0 | 420 | 25.423729 | 0.60240 | 0 | 327 | 1279 | 25.56685 | 0.9151 | 1 | 137 | 375 | 36.53333 | 0.9108 | 1 | 0 | 1590 | 0.0000000 | 0.09298 | 0 | 1428 | 1652 | 86.44068 | 0.8939 | 1 | 796 | 0 | 0.0000000 | 0.1224 | 0 | 384 | 48.2412060 | 0.9897 | 1 | 19 | 554 | 3.4296029 | 0.7145 | 0 | 45 | 554 | 8.122744 | 0.6556 | 0 | 0 | 1652 | 0.00000 | 0.3640 | 0 | 2.52440 | 0.5138 | 2 | 2.99308 | 0.7515 | 2 | 0.8939 | 0.8856 | 1 | 2.8462 | 0.6637 | 1 | 9.25758 | 0.6790 | 6 | 1382 | 748 | 549 | 742 | 1382 | 53.69030 | 0.9560 | 1 | 40 | 511 | 7.827789 | 0.7730 | 1 | 110 | 402 | 27.363184 | 0.71780 | 0 | 45 | 147 | 30.612245 | 0.23070 | 0 | 155 | 549 | 28.23315 | 0.47730 | 0 | 181 | 905 | 20.00000 | 0.8253 | 1 | 232 | 1382 | 16.787265 | 0.8813 | 1 | 164 | 11.866860 | 0.27170 | 0 | 250 | 18.089725 | 0.26290 | 0 | 258 | 1132.0000 | 22.79152 | 0.8368 | 1 | 99 | 279.0000 | 35.48387 | 0.9162 | 1 | 33 | 1275 | 2.5882353 | 0.64520 | 0 | 1347 | 1382.0000 | 97.46744 | 0.9681 | 1 | 748 | 0 | 0.0000000 | 0.1079 | 0 | 375 | 50.1336898 | 0.9922 | 1 | 0 | 549 | 0.0000000 | 0.09796 | 0 | 37 | 549.0000 | 6.739526 | 0.6039 | 0 | 0 | 1382 | 0.0000000 | 0.1831 | 0 | 3.91290 | 0.8785 | 4 | 2.93280 | 0.7342 | 2 | 0.9681 | 0.9599 | 1 | 1.98506 | 0.2471 | 1 | 9.79886 | 0.7570 | 8 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9521, Bullock County, Alabama | 19754 | 58200 | 18598 | 66900 | 22914.64 | 67512 | -4316.64 | -0.1883791 | -612 | -0.0090651 | NA | NA | NA | NA | NA |
| 01015000300 | 01015 | 000300 | AL | Alabama | Calhoun County | 3 | South Region | 6 | East South Central Division | 3074 | 1635 | 1330 | 1904 | 3067 | 62.08021 | 0.9710 | 1 | 293 | 1362 | 21.512482 | 0.96630 | 1 | 180 | 513 | 35.08772 | 0.65450 | 0 | 383 | 817 | 46.87882 | 0.55040 | 0 | 563 | 1330 | 42.33083 | 0.70280 | 0 | 720 | 2127 | 33.85049 | 0.9148 | 1 | 628 | 2835 | 22.151675 | 0.8076 | 1 | 380 | 12.361744 | 0.49340 | 0 | 713 | 23.194535 | 0.45030 | 0 | 647 | 2111 | 30.64898 | 0.9708 | 1 | 298 | 773 | 38.55110 | 0.9247 | 1 | 0 | 2878 | 0.0000000 | 0.09298 | 0 | 2623 | 3074 | 85.32856 | 0.8883 | 1 | 1635 | 148 | 9.0519878 | 0.6465 | 0 | 6 | 0.3669725 | 0.4502 | 0 | 68 | 1330 | 5.1127820 | 0.8082 | 1 | 303 | 1330 | 22.781955 | 0.9029 | 1 | 0 | 3074 | 0.00000 | 0.3640 | 0 | 4.36250 | 0.9430 | 4 | 2.93218 | 0.7233 | 2 | 0.8883 | 0.8800 | 1 | 3.1718 | 0.8070 | 2 | 11.35478 | 0.9009 | 9 | 2390 | 1702 | 1282 | 1287 | 2390 | 53.84937 | 0.9566 | 1 | 102 | 1066 | 9.568480 | 0.8541 | 1 | 158 | 609 | 25.944171 | 0.67520 | 0 | 286 | 673 | 42.496285 | 0.48560 | 0 | 444 | 1282 | 34.63339 | 0.66340 | 0 | 467 | 1685 | 27.71513 | 0.9180 | 1 | 369 | 2379 | 15.510719 | 0.8562 | 1 | 342 | 14.309623 | 0.40850 | 0 | 548 | 22.928870 | 0.57100 | 0 | 647 | 1831.0000 | 35.33588 | 0.9862 | 1 | 202 | 576.0000 | 35.06944 | 0.9130 | 1 | 16 | 2134 | 0.7497657 | 0.40690 | 0 | 1896 | 2390.0000 | 79.33054 | 0.8451 | 1 | 1702 | 96 | 5.6404230 | 0.5329 | 0 | 0 | 0.0000000 | 0.2186 | 0 | 0 | 1282 | 0.0000000 | 0.09796 | 0 | 186 | 1282.0000 | 14.508580 | 0.8308 | 1 | 43 | 2390 | 1.7991632 | 0.7727 | 1 | 4.24830 | 0.9395 | 4 | 3.28560 | 0.8773 | 2 | 0.8451 | 0.8379 | 1 | 2.45296 | 0.4602 | 2 | 10.83196 | 0.8718 | 9 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 3, Calhoun County, Alabama | 12211 | 41700 | 18299 | 51300 | 14164.76 | 48372 | 4134.24 | 0.2918680 | 2928 | 0.0605309 | NA | NA | Calhoun County, Alabama | Anniston-Oxford, AL MSA | C1150 |
| 01015000500 | 01015 | 000500 | AL | Alabama | Calhoun County | 3 | South Region | 6 | East South Central Division | 1731 | 1175 | 743 | 1042 | 1619 | 64.36072 | 0.9767 | 1 | 124 | 472 | 26.271186 | 0.98460 | 1 | 136 | 461 | 29.50108 | 0.48970 | 0 | 163 | 282 | 57.80142 | 0.79190 | 1 | 299 | 743 | 40.24226 | 0.64910 | 0 | 340 | 1270 | 26.77165 | 0.8389 | 1 | 460 | 1794 | 25.641026 | 0.8722 | 1 | 271 | 15.655690 | 0.70190 | 0 | 368 | 21.259388 | 0.32190 | 0 | 507 | 1449 | 34.98965 | 0.9885 | 1 | 150 | 386 | 38.86010 | 0.9269 | 1 | 0 | 1677 | 0.0000000 | 0.09298 | 0 | 1559 | 1731 | 90.06355 | 0.9123 | 1 | 1175 | 50 | 4.2553191 | 0.5128 | 0 | 4 | 0.3404255 | 0.4480 | 0 | 0 | 743 | 0.0000000 | 0.1238 | 0 | 122 | 743 | 16.419919 | 0.8473 | 1 | 0 | 1731 | 0.00000 | 0.3640 | 0 | 4.32150 | 0.9362 | 4 | 3.03218 | 0.7679 | 2 | 0.9123 | 0.9038 | 1 | 2.2959 | 0.3818 | 1 | 10.56188 | 0.8244 | 8 | 940 | 907 | 488 | 586 | 940 | 62.34043 | 0.9815 | 1 | 59 | 297 | 19.865320 | 0.9833 | 1 | 100 | 330 | 30.303030 | 0.79220 | 1 | 58 | 158 | 36.708861 | 0.34970 | 0 | 158 | 488 | 32.37705 | 0.60200 | 0 | 199 | 795 | 25.03145 | 0.8930 | 1 | 118 | 940 | 12.553192 | 0.7770 | 1 | 246 | 26.170213 | 0.90530 | 1 | 118 | 12.553192 | 0.08233 | 0 | 383 | 822.5089 | 46.56484 | 0.9984 | 1 | 30 | 197.8892 | 15.16000 | 0.5363 | 0 | 0 | 889 | 0.0000000 | 0.09479 | 0 | 898 | 940.3866 | 95.49264 | 0.9489 | 1 | 907 | 0 | 0.0000000 | 0.1079 | 0 | 2 | 0.2205072 | 0.4456 | 0 | 2 | 488 | 0.4098361 | 0.23670 | 0 | 146 | 487.6463 | 29.939736 | 0.9404 | 1 | 0 | 940 | 0.0000000 | 0.1831 | 0 | 4.23680 | 0.9379 | 4 | 2.61712 | 0.5593 | 2 | 0.9489 | 0.9409 | 1 | 1.91370 | 0.2196 | 1 | 9.71652 | 0.7468 | 8 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 5, Calhoun County, Alabama | 11742 | 38800 | 13571 | 38800 | 13620.72 | 45008 | -49.72 | -0.0036503 | -6208 | -0.1379310 | NA | NA | Calhoun County, Alabama | Anniston-Oxford, AL MSA | C1150 |
| 01015000600 | 01015 | 000600 | AL | Alabama | Calhoun County | 3 | South Region | 6 | East South Central Division | 2571 | 992 | 796 | 1394 | 2133 | 65.35396 | 0.9789 | 1 | 263 | 905 | 29.060773 | 0.98990 | 1 | 121 | 306 | 39.54248 | 0.75940 | 1 | 209 | 490 | 42.65306 | 0.44810 | 0 | 330 | 796 | 41.45729 | 0.68030 | 0 | 641 | 1556 | 41.19537 | 0.9554 | 1 | 416 | 1760 | 23.636364 | 0.8383 | 1 | 220 | 8.556982 | 0.24910 | 0 | 584 | 22.714897 | 0.41610 | 0 | 539 | 1353 | 39.83740 | 0.9955 | 1 | 243 | 466 | 52.14592 | 0.9783 | 1 | 30 | 2366 | 1.2679628 | 0.48990 | 0 | 1944 | 2571 | 75.61260 | 0.8440 | 1 | 992 | 164 | 16.5322581 | 0.7673 | 1 | 8 | 0.8064516 | 0.5110 | 0 | 46 | 796 | 5.7788945 | 0.8329 | 1 | 184 | 796 | 23.115578 | 0.9049 | 1 | 614 | 2571 | 23.88176 | 0.9734 | 1 | 4.44280 | 0.9548 | 4 | 3.12890 | 0.8088 | 2 | 0.8440 | 0.8362 | 1 | 3.9895 | 0.9792 | 4 | 12.40520 | 0.9696 | 11 | 1950 | 964 | 719 | 837 | 1621 | 51.63479 | 0.9467 | 1 | 157 | 652 | 24.079755 | 0.9922 | 1 | 22 | 364 | 6.043956 | 0.01547 | 0 | 129 | 355 | 36.338028 | 0.34200 | 0 | 151 | 719 | 21.00139 | 0.23030 | 0 | 363 | 1387 | 26.17159 | 0.9048 | 1 | 351 | 1613 | 21.760694 | 0.9435 | 1 | 249 | 12.769231 | 0.32090 | 0 | 356 | 18.256410 | 0.27140 | 0 | 332 | 1259.7041 | 26.35540 | 0.9135 | 1 | 136 | 435.6156 | 31.22018 | 0.8775 | 1 | 0 | 1891 | 0.0000000 | 0.09479 | 0 | 1463 | 1949.9821 | 75.02633 | 0.8219 | 1 | 964 | 14 | 1.4522822 | 0.3459 | 0 | 8 | 0.8298755 | 0.5269 | 0 | 19 | 719 | 2.6425591 | 0.61120 | 0 | 197 | 719.0542 | 27.397100 | 0.9316 | 1 | 329 | 1950 | 16.8717949 | 0.9655 | 1 | 4.01750 | 0.9001 | 4 | 2.47809 | 0.4764 | 2 | 0.8219 | 0.8149 | 1 | 3.38110 | 0.8712 | 2 | 10.69859 | 0.8583 | 9 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 6, Calhoun County, Alabama | 10958 | 48000 | 14036 | 43300 | 12711.28 | 55680 | 1324.72 | 0.1042161 | -12380 | -0.2223420 | NA | NA | Calhoun County, Alabama | Anniston-Oxford, AL MSA | C1150 |
| 01015002101 | 01015 | 002101 | AL | Alabama | Calhoun County | 3 | South Region | 6 | East South Central Division | 3872 | 1454 | 1207 | 1729 | 2356 | 73.38710 | 0.9916 | 1 | 489 | 2020 | 24.207921 | 0.97860 | 1 | 20 | 168 | 11.90476 | 0.02541 | 0 | 718 | 1039 | 69.10491 | 0.93320 | 1 | 738 | 1207 | 61.14333 | 0.96900 | 1 | 113 | 725 | 15.58621 | 0.6035 | 0 | 664 | 3943 | 16.839970 | 0.6495 | 0 | 167 | 4.313016 | 0.05978 | 0 | 238 | 6.146694 | 0.02255 | 0 | 264 | 2359 | 11.19118 | 0.3027 | 0 | 94 | 263 | 35.74144 | 0.9050 | 1 | 46 | 3769 | 1.2204829 | 0.48250 | 0 | 1601 | 3872 | 41.34814 | 0.6572 | 0 | 1454 | 761 | 52.3383769 | 0.9504 | 1 | 65 | 4.4704264 | 0.6738 | 0 | 5 | 1207 | 0.4142502 | 0.2791 | 0 | 113 | 1207 | 9.362055 | 0.7004 | 0 | 1516 | 3872 | 39.15289 | 0.9860 | 1 | 4.19220 | 0.9133 | 3 | 1.77253 | 0.1304 | 1 | 0.6572 | 0.6511 | 0 | 3.5897 | 0.9337 | 2 | 10.21163 | 0.7885 | 6 | 3238 | 1459 | 1014 | 1082 | 1836 | 58.93246 | 0.9735 | 1 | 251 | 1403 | 17.890235 | 0.9767 | 1 | 31 | 155 | 20.000000 | 0.44920 | 0 | 515 | 859 | 59.953434 | 0.85540 | 1 | 546 | 1014 | 53.84615 | 0.95350 | 1 | 134 | 916 | 14.62882 | 0.7033 | 0 | 251 | 3238 | 7.751699 | 0.5588 | 0 | 167 | 5.157505 | 0.03597 | 0 | 169 | 5.219271 | 0.02111 | 0 | 323 | 1667.0000 | 19.37612 | 0.7205 | 0 | 94 | 277.0000 | 33.93502 | 0.9040 | 1 | 0 | 3164 | 0.0000000 | 0.09479 | 0 | 1045 | 3238.0000 | 32.27301 | 0.5125 | 0 | 1459 | 607 | 41.6038382 | 0.9185 | 1 | 65 | 4.4551062 | 0.6949 | 0 | 24 | 1014 | 2.3668639 | 0.57900 | 0 | 85 | 1014.0000 | 8.382643 | 0.6775 | 0 | 1402 | 3238 | 43.2983323 | 0.9876 | 1 | 4.16580 | 0.9263 | 3 | 1.77637 | 0.1225 | 1 | 0.5125 | 0.5082 | 0 | 3.85750 | 0.9661 | 2 | 10.31217 | 0.8160 | 6 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 21.01, Calhoun County, Alabama | 4968 | 92000 | 9312 | 153500 | 5762.88 | 106720 | 3549.12 | 0.6158587 | 46780 | 0.4383433 | NA | NA | Calhoun County, Alabama | Anniston-Oxford, AL MSA | C1150 |
| 01015002300 | 01015 | 002300 | AL | Alabama | Calhoun County | 3 | South Region | 6 | East South Central Division | 3882 | 1861 | 1608 | 1366 | 3882 | 35.18805 | 0.7753 | 1 | 186 | 1539 | 12.085770 | 0.80740 | 1 | 284 | 1109 | 25.60866 | 0.35530 | 0 | 202 | 499 | 40.48096 | 0.39670 | 0 | 486 | 1608 | 30.22388 | 0.34700 | 0 | 727 | 2610 | 27.85441 | 0.8534 | 1 | 547 | 3706 | 14.759849 | 0.5669 | 0 | 716 | 18.444101 | 0.82530 | 1 | 904 | 23.286966 | 0.45720 | 0 | 719 | 2919 | 24.63172 | 0.8986 | 1 | 207 | 1191 | 17.38035 | 0.5923 | 0 | 0 | 3720 | 0.0000000 | 0.09298 | 0 | 490 | 3882 | 12.62236 | 0.3118 | 0 | 1861 | 38 | 2.0419130 | 0.4070 | 0 | 199 | 10.6931757 | 0.7836 | 1 | 52 | 1608 | 3.2338308 | 0.6986 | 0 | 166 | 1608 | 10.323383 | 0.7304 | 0 | 0 | 3882 | 0.00000 | 0.3640 | 0 | 3.35000 | 0.7384 | 3 | 2.86638 | 0.6919 | 2 | 0.3118 | 0.3089 | 0 | 2.9836 | 0.7289 | 1 | 9.51178 | 0.7100 | 6 | 3265 | 1774 | 1329 | 1103 | 3265 | 33.78254 | 0.7880 | 1 | 122 | 1422 | 8.579465 | 0.8131 | 1 | 101 | 844 | 11.966825 | 0.10960 | 0 | 126 | 485 | 25.979381 | 0.15930 | 0 | 227 | 1329 | 17.08051 | 0.11070 | 0 | 267 | 2122 | 12.58247 | 0.6388 | 0 | 328 | 3265 | 10.045942 | 0.6808 | 0 | 440 | 13.476263 | 0.36070 | 0 | 843 | 25.819296 | 0.74470 | 0 | 530 | 2422.0000 | 21.88274 | 0.8097 | 1 | 254 | 861.0000 | 29.50058 | 0.8574 | 1 | 0 | 3026 | 0.0000000 | 0.09479 | 0 | 811 | 3265.0000 | 24.83920 | 0.4221 | 0 | 1774 | 7 | 0.3945885 | 0.2444 | 0 | 338 | 19.0529876 | 0.8924 | 1 | 19 | 1329 | 1.4296464 | 0.44520 | 0 | 120 | 1329.0000 | 9.029345 | 0.7016 | 0 | 0 | 3265 | 0.0000000 | 0.1831 | 0 | 3.03140 | 0.6608 | 2 | 2.86729 | 0.7016 | 2 | 0.4221 | 0.4185 | 0 | 2.46670 | 0.4669 | 1 | 8.78749 | 0.6230 | 5 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 23, Calhoun County, Alabama | 15086 | 77500 | 21540 | 78500 | 17499.76 | 89900 | 4040.24 | 0.2308740 | -11400 | -0.1268076 | 120.54 | 131.82 | Calhoun County, Alabama | Anniston-Oxford, AL MSA | C1150 |
| 01023956700 | 01023 | 956700 | AL | Alabama | Choctaw County | 3 | South Region | 6 | East South Central Division | 3011 | 1772 | 1179 | 1715 | 3011 | 56.95782 | 0.9531 | 1 | 266 | 890 | 29.887640 | 0.99100 | 1 | 267 | 1035 | 25.79710 | 0.36240 | 0 | 79 | 144 | 54.86111 | 0.73440 | 0 | 346 | 1179 | 29.34690 | 0.31850 | 0 | 738 | 2053 | 35.94739 | 0.9287 | 1 | 543 | 2904 | 18.698347 | 0.7133 | 0 | 569 | 18.897376 | 0.84040 | 1 | 648 | 21.521089 | 0.33840 | 0 | 813 | 2273 | 35.76771 | 0.9901 | 1 | 252 | 771 | 32.68482 | 0.8778 | 1 | 0 | 2880 | 0.0000000 | 0.09298 | 0 | 2455 | 3011 | 81.53437 | 0.8712 | 1 | 1772 | 38 | 2.1444695 | 0.4136 | 0 | 485 | 27.3702032 | 0.9349 | 1 | 72 | 1179 | 6.1068702 | 0.8435 | 1 | 109 | 1179 | 9.245123 | 0.6964 | 0 | 0 | 3011 | 0.00000 | 0.3640 | 0 | 3.90460 | 0.8597 | 3 | 3.13968 | 0.8131 | 3 | 0.8712 | 0.8631 | 1 | 3.2524 | 0.8387 | 2 | 11.16788 | 0.8840 | 9 | 3335 | 1912 | 1362 | 1135 | 3313 | 34.25898 | 0.7948 | 1 | 188 | 1147 | 16.390584 | 0.9686 | 1 | 212 | 1058 | 20.037807 | 0.45090 | 0 | 27 | 304 | 8.881579 | 0.02679 | 0 | 239 | 1362 | 17.54772 | 0.12350 | 0 | 466 | 2537 | 18.36815 | 0.7948 | 1 | 495 | 3335 | 14.842579 | 0.8413 | 1 | 791 | 23.718141 | 0.85250 | 1 | 613 | 18.380810 | 0.27840 | 0 | 884 | 2714.0000 | 32.57185 | 0.9752 | 1 | 230 | 918.0000 | 25.05447 | 0.7925 | 1 | 25 | 3103 | 0.8056719 | 0.41920 | 0 | 2637 | 3335.0000 | 79.07046 | 0.8436 | 1 | 1912 | 0 | 0.0000000 | 0.1079 | 0 | 758 | 39.6443515 | 0.9799 | 1 | 16 | 1362 | 1.1747430 | 0.40060 | 0 | 75 | 1362.0000 | 5.506608 | 0.5316 | 0 | 8 | 3335 | 0.2398801 | 0.4965 | 0 | 3.52300 | 0.7901 | 4 | 3.31780 | 0.8870 | 3 | 0.8436 | 0.8365 | 1 | 2.51650 | 0.4924 | 1 | 10.20090 | 0.8033 | 9 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9567, Choctaw County, Alabama | 12737 | 60900 | 16852 | 63400 | 14774.92 | 70644 | 2077.08 | 0.1405815 | -7244 | -0.1025423 | NA | NA | NA | NA | NA |
| 01023957000 | 01023 | 957000 | AL | Alabama | Choctaw County | 3 | South Region | 6 | East South Central Division | 2567 | 1187 | 916 | 767 | 2567 | 29.87924 | 0.6933 | 0 | 145 | 1060 | 13.679245 | 0.86050 | 1 | 101 | 719 | 14.04729 | 0.04540 | 0 | 43 | 197 | 21.82741 | 0.09791 | 0 | 144 | 916 | 15.72052 | 0.02333 | 0 | 355 | 1704 | 20.83333 | 0.7366 | 0 | 289 | 2296 | 12.587108 | 0.4736 | 0 | 324 | 12.621737 | 0.51120 | 0 | 688 | 26.801714 | 0.68810 | 0 | 572 | 1746 | 32.76060 | 0.9809 | 1 | 121 | 636 | 19.02516 | 0.6414 | 0 | 5 | 2283 | 0.2190101 | 0.22520 | 0 | 1314 | 2567 | 51.18816 | 0.7225 | 0 | 1187 | 0 | 0.0000000 | 0.1224 | 0 | 335 | 28.2224094 | 0.9394 | 1 | 13 | 916 | 1.4192140 | 0.4834 | 0 | 70 | 916 | 7.641921 | 0.6353 | 0 | 0 | 2567 | 0.00000 | 0.3640 | 0 | 2.78733 | 0.5903 | 1 | 3.04680 | 0.7745 | 1 | 0.7225 | 0.7158 | 0 | 2.5445 | 0.5114 | 1 | 9.10113 | 0.6601 | 3 | 2077 | 1158 | 866 | 759 | 2072 | 36.63127 | 0.8256 | 1 | 61 | 780 | 7.820513 | 0.7726 | 1 | 106 | 735 | 14.421769 | 0.19760 | 0 | 11 | 131 | 8.396947 | 0.02525 | 0 | 117 | 866 | 13.51039 | 0.04053 | 0 | 351 | 1464 | 23.97541 | 0.8815 | 1 | 205 | 2077 | 9.870005 | 0.6729 | 0 | 402 | 19.354839 | 0.68820 | 0 | 496 | 23.880597 | 0.63430 | 0 | 466 | 1576.0000 | 29.56853 | 0.9544 | 1 | 154 | 612.0000 | 25.16340 | 0.7942 | 1 | 0 | 2002 | 0.0000000 | 0.09479 | 0 | 1018 | 2077.0000 | 49.01300 | 0.6638 | 0 | 1158 | 0 | 0.0000000 | 0.1079 | 0 | 439 | 37.9101900 | 0.9766 | 1 | 0 | 866 | 0.0000000 | 0.09796 | 0 | 42 | 866.0000 | 4.849884 | 0.4884 | 0 | 5 | 2077 | 0.2407318 | 0.4971 | 0 | 3.19313 | 0.7061 | 3 | 3.16589 | 0.8369 | 2 | 0.6638 | 0.6582 | 0 | 2.16796 | 0.3247 | 1 | 9.19078 | 0.6792 | 6 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 9570, Choctaw County, Alabama | 16224 | 51600 | 21740 | 74000 | 18819.84 | 59856 | 2920.16 | 0.1551639 | 14144 | 0.2363005 | NA | NA | NA | NA | NA |
| 01031010500 | 01031 | 010500 | AL | Alabama | Coffee County | 3 | South Region | 6 | East South Central Division | 4529 | 1950 | 1664 | 1649 | 4022 | 40.99950 | 0.8432 | 1 | 114 | 1424 | 8.005618 | 0.56260 | 0 | 309 | 1057 | 29.23368 | 0.48130 | 0 | 251 | 607 | 41.35091 | 0.41690 | 0 | 560 | 1664 | 33.65385 | 0.45740 | 0 | 1269 | 3370 | 37.65579 | 0.9387 | 1 | 516 | 4279 | 12.058892 | 0.4492 | 0 | 832 | 18.370501 | 0.82310 | 1 | 894 | 19.739457 | 0.23950 | 0 | 1023 | 3404 | 30.05288 | 0.9666 | 1 | 303 | 1112 | 27.24820 | 0.8108 | 1 | 43 | 4270 | 1.0070258 | 0.44510 | 0 | 1761 | 4529 | 38.88276 | 0.6383 | 0 | 1950 | 6 | 0.3076923 | 0.2576 | 0 | 276 | 14.1538462 | 0.8279 | 1 | 8 | 1664 | 0.4807692 | 0.2925 | 0 | 125 | 1664 | 7.512019 | 0.6289 | 0 | 507 | 4529 | 11.19452 | 0.9441 | 1 | 3.25110 | 0.7138 | 2 | 3.28510 | 0.8639 | 3 | 0.6383 | 0.6324 | 0 | 2.9510 | 0.7136 | 2 | 10.12550 | 0.7794 | 7 | 4815 | 2118 | 1731 | 1329 | 4470 | 29.73154 | 0.7256 | 0 | 147 | 1903 | 7.724645 | 0.7670 | 1 | 209 | 1256 | 16.640127 | 0.29310 | 0 | 208 | 475 | 43.789474 | 0.51620 | 0 | 417 | 1731 | 24.09012 | 0.33700 | 0 | 953 | 3728 | 25.56330 | 0.8985 | 1 | 668 | 4485 | 14.894091 | 0.8425 | 1 | 1053 | 21.869159 | 0.79500 | 1 | 766 | 15.908619 | 0.16760 | 0 | 1010 | 3719.0000 | 27.15784 | 0.9262 | 1 | 243 | 1133.0000 | 21.44748 | 0.7184 | 0 | 1 | 4577 | 0.0218484 | 0.19150 | 0 | 1643 | 4815.0000 | 34.12253 | 0.5321 | 0 | 2118 | 0 | 0.0000000 | 0.1079 | 0 | 475 | 22.4268178 | 0.9157 | 1 | 37 | 1731 | 2.1374928 | 0.55080 | 0 | 144 | 1731.0000 | 8.318891 | 0.6750 | 0 | 330 | 4815 | 6.8535826 | 0.9282 | 1 | 3.57060 | 0.8018 | 3 | 2.79870 | 0.6649 | 2 | 0.5321 | 0.5276 | 0 | 3.17760 | 0.7990 | 2 | 10.07900 | 0.7892 | 7 | 0 | 0 | 0 | 0 | 0 | Yes | Census Tract 105, Coffee County, Alabama | 14641 | 88000 | 21367 | 78100 | 16983.56 | 102080 | 4383.44 | 0.2580990 | -23980 | -0.2349138 | 128.88 | 137.26 | Coffee County, Alabama | Dothan-Enterprise-Ozark, AL CSA | CS222 |
Log NMTC and LIHTC Variables
svi_national_nmtc_df$Median_Income_10adj_log <- log(svi_national_nmtc_df$Median_Income_10adj)
svi_national_nmtc_df$Median_Income_19_log <- log(svi_national_nmtc_df$Median_Income_19)
svi_national_nmtc_df$Median_Home_Value_10adj_log = log(svi_national_nmtc_df$Median_Home_Value_10adj)
svi_national_nmtc_df$Median_Home_Value_19_log = log(svi_national_nmtc_df$Median_Home_Value_19)
svi_national_nmtc_df$housing_price_index10_log = log(svi_national_nmtc_df$housing_price_index10)
svi_national_nmtc_df$housing_price_index20_log = log(svi_national_nmtc_df$housing_price_index20)
svi_divisional_nmtc_df$Median_Income_10adj_log <- log(svi_divisional_nmtc_df$Median_Income_10adj)
svi_divisional_nmtc_df$Median_Income_19_log <- log(svi_divisional_nmtc_df$Median_Income_19)
svi_divisional_nmtc_df$Median_Home_Value_10adj_log = log(svi_divisional_nmtc_df$Median_Home_Value_10adj)
svi_divisional_nmtc_df$Median_Home_Value_19_log = log(svi_divisional_nmtc_df$Median_Home_Value_19)
svi_divisional_nmtc_df$housing_price_index10_log = log(svi_divisional_nmtc_df$housing_price_index10)
svi_divisional_nmtc_df$housing_price_index20_log = log(svi_divisional_nmtc_df$housing_price_index20)
svi_national_lihtc_df$Median_Income_10adj_log <- log(svi_national_lihtc_df$Median_Income_10adj)
svi_national_lihtc_df$Median_Income_19_log <- log(svi_national_lihtc_df$Median_Income_19)
svi_national_lihtc_df$Median_Home_Value_10adj_log = log(svi_national_lihtc_df$Median_Home_Value_10adj)
svi_national_lihtc_df$Median_Home_Value_19_log = log(svi_national_lihtc_df$Median_Home_Value_19)
svi_national_lihtc_df$housing_price_index10_log = log(svi_national_lihtc_df$housing_price_index10)
svi_national_lihtc_df$housing_price_index20_log = log(svi_national_lihtc_df$housing_price_index20)
svi_divisional_lihtc_df$Median_Income_10adj_log <- log(svi_divisional_lihtc_df$Median_Income_10adj)
svi_divisional_lihtc_df$Median_Income_19_log <- log(svi_divisional_lihtc_df$Median_Income_19)
svi_divisional_lihtc_df$Median_Home_Value_10adj_log = log(svi_divisional_lihtc_df$Median_Home_Value_10adj)
svi_divisional_lihtc_df$Median_Home_Value_19_log = log(svi_divisional_lihtc_df$Median_Home_Value_19)
svi_divisional_lihtc_df$housing_price_index10_log = log(svi_divisional_lihtc_df$housing_price_index10)
svi_divisional_lihtc_df$housing_price_index20_log = log(svi_divisional_lihtc_df$housing_price_index20)
NMTC Variable Distribution: Mountain Division
SVI Theme 1: Socioeconomic Status
hist(svi_divisional_nmtc_df$F_THEME1_10)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME1_10)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME1_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME1_10, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME1_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME1_10)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME1_10))))
## [1] "Absolute Skewness: 0.0249901327808313"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME1_10))))
## [1] "Absolute Excess Kurtosis: 1.12999825726"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME1_10) < mean(svi_divisional_nmtc_df$F_THEME1_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2020
hist(svi_divisional_nmtc_df$F_THEME1_20)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME1_20)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME1_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME1_20, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME1_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME1_20)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME1_20))))
## [1] "Absolute Skewness: 0.0216149135904862"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME1_20))))
## [1] "Absolute Excess Kurtosis: 1.03461573701947"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME1_20) < mean(svi_divisional_nmtc_df$F_THEME1_20)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
SVI THeme 2: Household Characteristics
2010
hist(svi_divisional_nmtc_df$F_THEME2_10)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME2_10)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME2_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME2_10, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME2_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME2_10)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME2_10))))
## [1] "Absolute Skewness: 0.00100423682188465"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME2_10))))
## [1] "Absolute Excess Kurtosis: 0.651194090353722"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME2_10) < mean(svi_divisional_nmtc_df$F_THEME2_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2020
hist(svi_divisional_nmtc_df$F_THEME2_20)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME2_20)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME2_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME2_20, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME2_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME2_20)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME2_20))))
## [1] "Absolute Skewness: 0.0215143038130277"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME2_20))))
## [1] "Absolute Excess Kurtosis: 0.701346689837882"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME2_20) < mean(svi_divisional_nmtc_df$F_THEME2_20)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
SVI Theme 3: Racial & Ethnic Minority Status
2010
hist(svi_divisional_nmtc_df$F_THEME3_10)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME3_10)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME3_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME3_10, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME1_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME3_10)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME3_10))))
## [1] "Absolute Skewness: 0.0309634623783316"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME3_10))))
## [1] "Absolute Excess Kurtosis: 1.99904126399755"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME3_10) < mean(svi_divisional_nmtc_df$F_THEME3_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
table(svi_divisional_nmtc_df$F_THEME3_10)
##
## 0 1
## 984 954
2020
hist(svi_divisional_nmtc_df$F_THEME3_20)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME3_20)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME3_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME3_20, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME3_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME3_20)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME3_20))))
## [1] "Absolute Skewness: 0.0805606315825733"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME3_20))))
## [1] "Absolute Excess Kurtosis: 1.99350998463902"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME3_20) < mean(svi_divisional_nmtc_df$F_THEME3_20)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
table(svi_divisional_nmtc_df$F_THEME3_20)
##
## 0 1
## 1008 930
SVI Theme 4: Housing Type & Transportation
2010
hist(svi_divisional_nmtc_df$F_THEME4_10)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME4_10)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME4_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME4_10, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME4_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME4_10)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME4_10))))
## [1] "Absolute Skewness: 0.0628118773173425"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME4_10))))
## [1] "Absolute Excess Kurtosis: 0.578223205433793"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME4_10) < mean(svi_divisional_nmtc_df$F_THEME4_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2020
hist(svi_divisional_nmtc_df$F_THEME4_20)
plotNormalHistogram(svi_divisional_nmtc_df$F_THEME4_20)
ggdensity(svi_divisional_nmtc_df, x = "F_THEME4_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_THEME4_20, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_THEME4_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_THEME4_20)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_THEME4_20))))
## [1] "Absolute Skewness: 0.0605950491829714"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_THEME4_20))))
## [1] "Absolute Excess Kurtosis: 0.658673836104457"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_THEME4_20) < mean(svi_divisional_nmtc_df$F_THEME4_20)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
SVI OVerall
2010
hist(svi_divisional_nmtc_df$F_TOTAL_10)
plotNormalHistogram(svi_divisional_nmtc_df$F_TOTAL_10)
ggdensity(svi_divisional_nmtc_df, x = "F_TOTAL_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_TOTAL_10, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_TOTAL_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_TOTAL_10)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_TOTAL_10))))
## [1] "Absolute Skewness: 0.0311483749255969"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_TOTAL_10))))
## [1] "Absolute Excess Kurtosis: 1.04070433814952"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_TOTAL_10) < mean(svi_divisional_nmtc_df$F_TOTAL_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2020
hist(svi_divisional_nmtc_df$F_TOTAL_20)
plotNormalHistogram(svi_divisional_nmtc_df$F_TOTAL_20)
ggdensity(svi_divisional_nmtc_df, x = "F_TOTAL_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$F_TOTAL_20, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$F_TOTAL_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$F_TOTAL_20)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$F_TOTAL_20))))
## [1] "Absolute Skewness: 0.0629866656842071"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$F_TOTAL_20))))
## [1] "Absolute Excess Kurtosis: 0.878387884554749"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$F_TOTAL_20) < mean(svi_divisional_nmtc_df$F_TOTAL_20)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Median Income
2010
options(scipen = 999)
hist(svi_divisional_nmtc_df$Median_Income_10adj)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Income_10adj)
ggdensity(svi_divisional_nmtc_df, x = "Median_Income_10adj", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$Median_Income_10adj, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Income_10adj, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Income_10adj)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Income_10adj, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.139463092047866"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Income_10adj, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.652592362975045"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Income_10adj, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Income_10adj, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2010 Log
hist(svi_divisional_nmtc_df$Median_Income_10adj_log)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Income_10adj_log)
ggdensity(svi_divisional_nmtc_df, x = "Median_Income_10adj_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$Median_Income_10adj_log, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Income_10adj_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Income_10adj_log)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Income_10adj_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.42384668286417"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Income_10adj_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 5.55272518758958"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Income_10adj_log, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Income_10adj_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2019
options(scipen = 999)
hist(svi_divisional_nmtc_df$Median_Income_19)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Income_19)
ggdensity(svi_divisional_nmtc_df, x = "Median_Income_19", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_nmtc_df$Median_Income_19, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Income_19, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Income_19)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Income_19, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.124785761521551"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Income_19, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.973068468347"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Income_19, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Income_19, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Median Home Value
2010
hist(svi_divisional_nmtc_df$Median_Home_Value_10adj)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Home_Value_10adj)
ggdensity(svi_divisional_nmtc_df, x = "Median_Home_Value_10adj", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 30 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 30 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$Median_Home_Value_10adj, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Home_Value_10adj, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Home_Value_10adj)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Home_Value_10adj, na.rm = TRUE))))
## [1] "Absolute Skewness: 2.29498564482883"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Home_Value_10adj, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 16.4426441276446"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Home_Value_10adj, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Home_Value_10adj, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2010 Log
hist(svi_divisional_nmtc_df$Median_Home_Value_10adj_log)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Home_Value_10adj_log)
ggdensity(svi_divisional_nmtc_df, x = "Median_Home_Value_10adj_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 30 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 30 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$Median_Home_Value_10adj_log, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Home_Value_10adj_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Home_Value_10adj_log)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Home_Value_10adj_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.17511485647903"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Home_Value_10adj_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 3.40043121085217"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Home_Value_10adj_log, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Home_Value_10adj_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2019
hist(svi_divisional_nmtc_df$Median_Home_Value_19)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Home_Value_19)
ggdensity(svi_divisional_nmtc_df, x = "Median_Home_Value_19", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$Median_Home_Value_19, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Home_Value_19, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Home_Value_19)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Home_Value_19, na.rm = TRUE))))
## [1] "Absolute Skewness: 2.60320862844623"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Home_Value_19, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 18.5791808764468"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Home_Value_19, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Home_Value_19, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2019 Log
hist(svi_divisional_nmtc_df$Median_Home_Value_19_log)
plotNormalHistogram(svi_divisional_nmtc_df$Median_Home_Value_19_log)
ggdensity(svi_divisional_nmtc_df, x = "Median_Home_Value_19_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$Median_Home_Value_19_log, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$Median_Home_Value_19_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$Median_Home_Value_19_log)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$Median_Home_Value_19_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.862701684939476"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$Median_Home_Value_19_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 2.58686759381741"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$Median_Home_Value_19_log, na.rm = TRUE) < mean(svi_divisional_nmtc_df$Median_Home_Value_19_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Housing Price Index
*2010
hist(svi_divisional_nmtc_df$housing_price_index10)
plotNormalHistogram(svi_divisional_nmtc_df$housing_price_index10)
ggdensity(svi_divisional_nmtc_df, x = "housing_price_index10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 857 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 857 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$housing_price_index10, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$housing_price_index10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$housing_price_index10)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$housing_price_index10, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.13858022197036"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$housing_price_index10, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.13858022197036"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$housing_price_index10, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 2.36895681000769"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$housing_price_index10, na.rm = TRUE) < mean(svi_divisional_nmtc_df$housing_price_index10, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2010 Log
hist(svi_divisional_nmtc_df$housing_price_index10_log)
plotNormalHistogram(svi_divisional_nmtc_df$housing_price_index10_log)
ggdensity(svi_divisional_nmtc_df, x = "housing_price_index10_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 857 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 857 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$housing_price_index10_log, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$housing_price_index10_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$housing_price_index10_log)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$housing_price_index10_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.0435644823884166"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$housing_price_index10_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.0142493700199102"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$housing_price_index10_log, na.rm = TRUE) < mean(svi_divisional_nmtc_df$housing_price_index10_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020
hist(svi_divisional_nmtc_df$housing_price_index20)
plotNormalHistogram(svi_divisional_nmtc_df$housing_price_index20)
ggdensity(svi_divisional_nmtc_df, x = "housing_price_index20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 722 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 722 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$housing_price_index20, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$housing_price_index20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$housing_price_index20)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$housing_price_index20, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.33009328321753"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$housing_price_index20, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 3.08862562179683"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$housing_price_index20, na.rm = TRUE) < mean(svi_divisional_nmtc_df$housing_price_index20, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020 Log
hist(svi_divisional_nmtc_df$housing_price_index20_log)
plotNormalHistogram(svi_divisional_nmtc_df$housing_price_index20_log)
ggdensity(svi_divisional_nmtc_df, x = "housing_price_index20_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 722 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 722 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_nmtc_df$housing_price_index20_log, pch = 1, frame = FALSE)
qqline(svi_divisional_nmtc_df$housing_price_index20_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_nmtc_df$housing_price_index20_log)))
## [1] "Length: 1938"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_nmtc_df$housing_price_index20_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.0722867843904414"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_nmtc_df$housing_price_index20_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.0755339224588782"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_nmtc_df$housing_price_index20_log, na.rm = TRUE) < mean(svi_divisional_nmtc_df$housing_price_index20_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
LIHTC Variable Distribution: Mountain Division
SVI Theme 1: Socioeconomic Status
hist(svi_divisional_lihtc_df$F_THEME1_10)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME1_10)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME1_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME1_10, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME1_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME1_10)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME1_10))))
## [1] "Absolute Skewness: 0.698742055986755"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME1_10))))
## [1] "Absolute Excess Kurtosis: 0.299137459182033"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME1_10) < mean(svi_divisional_lihtc_df$F_THEME1_10)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020
hist(svi_divisional_lihtc_df$F_THEME1_20)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME1_20)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME1_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME1_20, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME1_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME1_20)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME1_20))))
## [1] "Absolute Skewness: 0.591300029458139"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME1_20))))
## [1] "Absolute Excess Kurtosis: 0.587568327007457"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME1_20) < mean(svi_divisional_lihtc_df$F_THEME1_20)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
SVI THeme 2: Household Characteristics
2010
hist(svi_divisional_lihtc_df$F_THEME2_10)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME2_10)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME2_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME2_10, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME2_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME2_10)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME2_10))))
## [1] "Absolute Skewness: 0.282745286649261"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME2_10))))
## [1] "Absolute Excess Kurtosis: 0.916403920458291"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME2_10) < mean(svi_divisional_lihtc_df$F_THEME2_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2020
hist(svi_divisional_lihtc_df$F_THEME2_20)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME2_20)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME2_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME2_20, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME2_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME2_20)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME2_20))))
## [1] "Absolute Skewness: 0.323066588839606"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME2_20))))
## [1] "Absolute Excess Kurtosis: 0.949799629112459"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME2_20) < mean(svi_divisional_lihtc_df$F_THEME2_20)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
SVI Theme 3: Racial & Ethnic Minority Status
2010
hist(svi_divisional_lihtc_df$F_THEME3_10)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME3_10)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME3_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME3_10, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME1_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME3_10)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME3_10))))
## [1] "Absolute Skewness: 0.812149380607502"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME3_10))))
## [1] "Absolute Excess Kurtosis: 1.34041338357885"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME3_10) < mean(svi_divisional_lihtc_df$F_THEME3_10)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
table(svi_divisional_lihtc_df$F_THEME3_10)
##
## 0 1
## 63 139
2020
hist(svi_divisional_lihtc_df$F_THEME3_20)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME3_20)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME3_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME3_20, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME3_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME3_20)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME3_20))))
## [1] "Absolute Skewness: 0.812149380607502"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME3_20))))
## [1] "Absolute Excess Kurtosis: 1.34041338357885"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME3_20) < mean(svi_divisional_lihtc_df$F_THEME3_20)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
table(svi_divisional_lihtc_df$F_THEME3_20)
##
## 0 1
## 63 139
SVI Theme 4: Housing Type & Transportation
2010
hist(svi_divisional_lihtc_df$F_THEME4_10)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME4_10)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME4_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME4_10, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME4_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME4_10)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME4_10))))
## [1] "Absolute Skewness: 0.314984102241371"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME4_10))))
## [1] "Absolute Excess Kurtosis: 0.215212929257489"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME4_10) < mean(svi_divisional_lihtc_df$F_THEME4_10)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020
hist(svi_divisional_lihtc_df$F_THEME4_20)
plotNormalHistogram(svi_divisional_lihtc_df$F_THEME4_20)
ggdensity(svi_divisional_lihtc_df, x = "F_THEME4_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_THEME4_20, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_THEME4_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_THEME4_20)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_THEME4_20))))
## [1] "Absolute Skewness: 0.192855546387606"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_THEME4_20))))
## [1] "Absolute Excess Kurtosis: 0.327891361511281"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_THEME4_20) < mean(svi_divisional_lihtc_df$F_THEME4_20)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
SVI Overall
2010
hist(svi_divisional_lihtc_df$F_TOTAL_10)
plotNormalHistogram(svi_divisional_lihtc_df$F_TOTAL_10)
ggdensity(svi_divisional_lihtc_df, x = "F_TOTAL_10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_TOTAL_10, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_TOTAL_10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_TOTAL_10)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_TOTAL_10))))
## [1] "Absolute Skewness: 0.525398616902496"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_TOTAL_10))))
## [1] "Absolute Excess Kurtosis: 0.467799904292678"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_TOTAL_10) < mean(svi_divisional_lihtc_df$F_TOTAL_10)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020
hist(svi_divisional_lihtc_df$F_TOTAL_20)
plotNormalHistogram(svi_divisional_lihtc_df$F_TOTAL_20)
ggdensity(svi_divisional_lihtc_df, x = "F_TOTAL_20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$F_TOTAL_20, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$F_TOTAL_20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$F_TOTAL_20)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$F_TOTAL_20))))
## [1] "Absolute Skewness: 0.430674795613127"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$F_TOTAL_20))))
## [1] "Absolute Excess Kurtosis: 0.280822546693426"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$F_TOTAL_20) < mean(svi_divisional_lihtc_df$F_TOTAL_20)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Median Income
2010
options(scipen = 999)
hist(svi_divisional_lihtc_df$Median_Income_10adj)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Income_10adj)
ggdensity(svi_divisional_lihtc_df, x = "Median_Income_10adj", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$Median_Income_10adj, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Income_10adj, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Income_10adj)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Income_10adj, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.00188005391528848"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Income_10adj, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.991594713590978"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Income_10adj, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Income_10adj, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2010 Log
hist(svi_divisional_lihtc_df$Median_Income_10adj_log)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Income_10adj_log)
ggdensity(svi_divisional_lihtc_df, x = "Median_Income_10adj_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$Median_Income_10adj_log, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Income_10adj_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Income_10adj_log)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Income_10adj_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.54255461177144"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Income_10adj_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 2.73888280996131"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Income_10adj_log, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Income_10adj_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2019
options(scipen = 999)
hist(svi_divisional_lihtc_df$Median_Income_19)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Income_19)
ggdensity(svi_divisional_lihtc_df, x = "Median_Income_19", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
qqnorm(svi_divisional_lihtc_df$Median_Income_19, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Income_19, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Income_19)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Income_19, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.738967218711519"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Income_19, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 3.96758907065596"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Income_19, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Income_19, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Median Home Value
2010
hist(svi_divisional_lihtc_df$Median_Home_Value_10adj)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Home_Value_10adj)
ggdensity(svi_divisional_lihtc_df, x = "Median_Home_Value_10adj", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 9 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 9 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$Median_Home_Value_10adj, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Home_Value_10adj, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Home_Value_10adj)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Home_Value_10adj, na.rm = TRUE))))
## [1] "Absolute Skewness: 2.9478613739634"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Home_Value_10adj, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 13.6859110055077"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Home_Value_10adj, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Home_Value_10adj, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2010 Log
hist(svi_divisional_lihtc_df$Median_Home_Value_10adj_log)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Home_Value_10adj_log)
ggdensity(svi_divisional_lihtc_df, x = "Median_Home_Value_10adj_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 9 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 9 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$Median_Home_Value_10adj_log, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Home_Value_10adj_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Home_Value_10adj_log)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Home_Value_10adj_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.399708664679192"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Home_Value_10adj_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 1.67692481223881"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Home_Value_10adj_log, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Home_Value_10adj_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2019
hist(svi_divisional_lihtc_df$Median_Home_Value_19)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Home_Value_19)
ggdensity(svi_divisional_lihtc_df, x = "Median_Home_Value_19", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 14 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 14 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$Median_Home_Value_19, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Home_Value_19, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Home_Value_19)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Home_Value_19, na.rm = TRUE))))
## [1] "Absolute Skewness: 3.19090980091081"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Home_Value_19, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 17.6985347895785"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Home_Value_19, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Home_Value_19, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: FALSE"
2019 Log
hist(svi_divisional_lihtc_df$Median_Home_Value_19_log)
plotNormalHistogram(svi_divisional_lihtc_df$Median_Home_Value_19_log)
ggdensity(svi_divisional_lihtc_df, x = "Median_Home_Value_19_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 14 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 14 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$Median_Home_Value_19_log, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$Median_Home_Value_19_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$Median_Home_Value_19_log)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$Median_Home_Value_19_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.0237161694371718"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$Median_Home_Value_19_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.202114576132213"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$Median_Home_Value_19_log, na.rm = TRUE) < mean(svi_divisional_lihtc_df$Median_Home_Value_19_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Housing Price Index
*2010
hist(svi_divisional_lihtc_df$housing_price_index10)
plotNormalHistogram(svi_divisional_lihtc_df$housing_price_index10)
ggdensity(svi_divisional_lihtc_df, x = "housing_price_index10", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 136 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 136 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$housing_price_index10, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$housing_price_index10, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$housing_price_index10)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$housing_price_index10, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.45735350547226"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$housing_price_index10, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.45735350547226"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$housing_price_index10, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 2.4013271457039"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$housing_price_index10, na.rm = TRUE) < mean(svi_divisional_lihtc_df$housing_price_index10, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2010 Log
hist(svi_divisional_lihtc_df$housing_price_index10_log)
plotNormalHistogram(svi_divisional_lihtc_df$housing_price_index10_log)
ggdensity(svi_divisional_lihtc_df, x = "housing_price_index10_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 136 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 136 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$housing_price_index10_log, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$housing_price_index10_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$housing_price_index10_log)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$housing_price_index10_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.323584982353486"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$housing_price_index10_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.235071725246949"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$housing_price_index10_log, na.rm = TRUE) < mean(svi_divisional_lihtc_df$housing_price_index10_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020
hist(svi_divisional_lihtc_df$housing_price_index20)
plotNormalHistogram(svi_divisional_lihtc_df$housing_price_index20)
ggdensity(svi_divisional_lihtc_df, x = "housing_price_index20", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 113 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 113 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$housing_price_index20, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$housing_price_index20, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$housing_price_index20)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$housing_price_index20, na.rm = TRUE))))
## [1] "Absolute Skewness: 1.48182201048028"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$housing_price_index20, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 2.32450252812465"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$housing_price_index20, na.rm = TRUE) < mean(svi_divisional_lihtc_df$housing_price_index20, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
2020 Log
hist(svi_divisional_lihtc_df$housing_price_index20_log)
plotNormalHistogram(svi_divisional_lihtc_df$housing_price_index20_log)
ggdensity(svi_divisional_lihtc_df, x = "housing_price_index20_log", fill = "lightgray") +
stat_overlay_normal_density(color = "red", linetype = "dashed")
## Warning: Removed 113 rows containing non-finite outside the scale range
## (`stat_density()`).
## Warning: Removed 113 rows containing non-finite outside the scale range
## (`stat_overlay_normal_density()`).
qqnorm(svi_divisional_lihtc_df$housing_price_index20_log, pch = 1, frame = FALSE)
qqline(svi_divisional_lihtc_df$housing_price_index20_log, col = "steelblue", lwd = 2)
# Statistics
print(paste0("Length: ", length(svi_divisional_lihtc_df$housing_price_index20_log)))
## [1] "Length: 202"
print(paste0("Absolute Skewness: ", abs(skewness(svi_divisional_lihtc_df$housing_price_index20_log, na.rm = TRUE))))
## [1] "Absolute Skewness: 0.25859338485172"
print(paste0("Absolute Excess Kurtosis: ", abs(3 - kurtosis(svi_divisional_lihtc_df$housing_price_index20_log, na.rm = TRUE))))
## [1] "Absolute Excess Kurtosis: 0.237165858523208"
print(paste0("Standard deviation is less than 1/2 mean: ", sd(svi_divisional_lihtc_df$housing_price_index20_log, na.rm = TRUE) < mean(svi_divisional_lihtc_df$housing_price_index20_log, na.rm = TRUE)/2))
## [1] "Standard deviation is less than 1/2 mean: TRUE"
Differences-in-Differences Models
NMTC Evaluation
Divisional SVI
# Create 2010 df, create post variable and set to 0, create year variable and set to 2010
nmtc_did10_div_svi <- svi_divisional_nmtc_df %>%
select(GEOID_2010_trt, cbsa, F_THEME1_10, F_THEME2_10, F_THEME3_10, F_THEME4_10, F_TOTAL_10, nmtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "nmtc_flag",
"SVI_FLAG_COUNT_SES" = "F_THEME1_10",
"SVI_FLAG_COUNT_HHCHAR" = "F_THEME2_10",
"SVI_FLAG_COUNT_REM" = "F_THEME3_10",
"SVI_FLAG_COUNT_HOUSETRANSPT" = "F_THEME4_10",
"SVI_FLAG_COUNT_OVERALL" = "F_TOTAL_10")
nrow(nmtc_did10_div_svi)
## [1] 1938
# Create 2020 df, create post variable and set to 1, create year variable and set to 2020
nmtc_did20_div_svi <- svi_divisional_nmtc_df %>%
select(GEOID_2010_trt, cbsa, F_THEME1_20, F_THEME2_20, F_THEME3_20, F_THEME4_20, F_TOTAL_20, nmtc_flag) %>%
mutate(post = 1,
year = 2020) %>%
rename("treat" = "nmtc_flag",
"SVI_FLAG_COUNT_SES" = "F_THEME1_20",
"SVI_FLAG_COUNT_HHCHAR" = "F_THEME2_20",
"SVI_FLAG_COUNT_REM" = "F_THEME3_20",
"SVI_FLAG_COUNT_HOUSETRANSPT" = "F_THEME4_20",
"SVI_FLAG_COUNT_OVERALL" = "F_TOTAL_20"
)
nrow(nmtc_did20_div_svi)
## [1] 1938
nmtc_diff_in_diff_div_svi <- bind_rows(nmtc_did10_div_svi, nmtc_did20_div_svi)
nmtc_diff_in_diff_div_svi <- nmtc_diff_in_diff_div_svi %>% arrange(post, treat, GEOID_2010_trt)
nrow(nmtc_diff_in_diff_div_svi)
## [1] 3876
Divisional Median Income
# Create 2010 df, create post variable and set to 0, create year variable and set to 2010, remove any tracts that don't have data for 2010 and 2019
nmtc_did10_div_inc <- svi_divisional_nmtc_df %>%
filter(!is.na(Median_Income_10adj_log)) %>% filter(!is.na(Median_Income_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Income_10adj_log, nmtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "nmtc_flag",
"MEDIAN_INCOME" = "Median_Income_10adj_log")
nrow(nmtc_did10_div_inc)
## [1] 1938
# Create 2019 df, create post variable and set to 1, create year variable and set to 2019, remove any tracts that don't have data for 2010 and 2019
nmtc_did19_div_inc <- svi_divisional_nmtc_df %>%
filter(!is.na(Median_Income_10adj_log)) %>% filter(!is.na(Median_Income_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Income_19_log, nmtc_flag) %>%
mutate(post = 1,
year = 2019) %>%
rename("treat" = "nmtc_flag",
"MEDIAN_INCOME" = "Median_Income_19_log")
nrow(nmtc_did19_div_inc)
## [1] 1938
nmtc_diff_in_diff_div_inc <- bind_rows(nmtc_did10_div_inc, nmtc_did19_div_inc)
nmtc_diff_in_diff_div_inc <- nmtc_diff_in_diff_div_inc %>% arrange(post, treat, GEOID_2010_trt)
nrow(nmtc_diff_in_diff_div_inc)
## [1] 3876
nmtc_diff_in_diff_div_svi %>% head() %>% kbl() %>% kable_styling() %>% scroll_box(width = "100%")
| GEOID_2010_trt | cbsa | SVI_FLAG_COUNT_SES | SVI_FLAG_COUNT_HHCHAR | SVI_FLAG_COUNT_REM | SVI_FLAG_COUNT_HOUSETRANSPT | SVI_FLAG_COUNT_OVERALL | treat | post | year |
|---|---|---|---|---|---|---|---|---|---|
| 04001942600 | NA | 2 | 4 | 1 | 3 | 10 | 0 | 0 | 2010 |
| 04001942700 | NA | 4 | 4 | 1 | 3 | 12 | 0 | 0 | 2010 |
| 04001944000 | NA | 3 | 1 | 1 | 3 | 8 | 0 | 0 | 2010 |
| 04001944100 | NA | 4 | 4 | 1 | 3 | 12 | 0 | 0 | 2010 |
| 04001944202 | NA | 4 | 3 | 1 | 4 | 12 | 0 | 0 | 2010 |
| 04001944300 | NA | 4 | 4 | 1 | 4 | 13 | 0 | 0 | 2010 |
Divisional Home Value
nmtc_did10_div_mhv <- svi_divisional_nmtc_df %>%
filter(!is.na(Median_Home_Value_10adj_log)) %>% filter(!is.na(Median_Home_Value_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Home_Value_10adj_log, nmtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "nmtc_flag",
"MEDIAN_HOME_VALUE" = "Median_Home_Value_10adj_log")
nrow(nmtc_did10_div_mhv)
## [1] 1882
nmtc_did19_div_mhv <- svi_divisional_nmtc_df %>%
filter(!is.na(Median_Home_Value_10adj_log)) %>% filter(!is.na(Median_Home_Value_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Home_Value_19_log, nmtc_flag) %>%
mutate(post = 1,
year = 2019) %>%
rename("treat" = "nmtc_flag",
"MEDIAN_HOME_VALUE" = "Median_Home_Value_19_log")
nrow(nmtc_did19_div_mhv)
## [1] 1882
nmtc_diff_in_diff_div_mhv <- bind_rows(nmtc_did10_div_mhv, nmtc_did19_div_mhv)
nmtc_diff_in_diff_div_mhv <- nmtc_diff_in_diff_div_mhv %>% arrange(post, treat, GEOID_2010_trt)
nrow(nmtc_diff_in_diff_div_mhv)
## [1] 3764
Divisional House Price Index
nmtc_did10_div_hpi <- svi_divisional_nmtc_df %>%
filter(!is.na(housing_price_index10_log)) %>% filter(!is.na(housing_price_index20_log)) %>%
select(GEOID_2010_trt, cbsa, housing_price_index10_log, nmtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "nmtc_flag",
"HOUSE_PRICE_INDEX" = "housing_price_index10_log")
nrow(nmtc_did10_div_hpi)
## [1] 1080
nmtc_did20_div_hpi <- svi_divisional_nmtc_df %>%
filter(!is.na(housing_price_index10_log)) %>% filter(!is.na(housing_price_index20_log)) %>%
select(GEOID_2010_trt, cbsa, housing_price_index20_log, nmtc_flag) %>%
mutate(post = 1,
year = 2020) %>%
rename("treat" = "nmtc_flag",
"HOUSE_PRICE_INDEX" = "housing_price_index20_log")
nrow(nmtc_did20_div_hpi)
## [1] 1080
nmtc_diff_in_diff_div_hpi <- bind_rows(nmtc_did10_div_hpi, nmtc_did20_div_hpi)
nmtc_diff_in_diff_div_hpi <- nmtc_diff_in_diff_div_hpi %>% arrange(post, treat, GEOID_2010_trt)
nrow(nmtc_diff_in_diff_div_hpi)
## [1] 2160
NMTC Divisional Model
# SVI & Economic Models
m1_nmtc_div <- lm( SVI_FLAG_COUNT_SES ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_svi )
m2_nmtc_div <- lm( SVI_FLAG_COUNT_HHCHAR ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_svi )
m3_nmtc_div <- lm( SVI_FLAG_COUNT_REM ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_svi )
m4_nmtc_div <- lm( SVI_FLAG_COUNT_HOUSETRANSPT ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_svi )
m5_nmtc_div <- lm( SVI_FLAG_COUNT_OVERALL ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_svi)
m6_nmtc_div <- lm( MEDIAN_INCOME ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_inc )
m7_nmtc_div <- lm( MEDIAN_HOME_VALUE ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_mhv )
m8_nmtc_div <- lm( HOUSE_PRICE_INDEX ~ treat + post + treat*post + cbsa, data=nmtc_diff_in_diff_div_hpi )
# Add all models to a list
models <- list(
"SES" = m1_nmtc_div,
"HHChar" = m2_nmtc_div,
"REM" = m3_nmtc_div,
"HOUSETRANSPT" = m4_nmtc_div,
"OVERALL" = m5_nmtc_div,
"Median Income (USD, logged)" = m6_nmtc_div,
"Median Home Value (USD, logged)" = m7_nmtc_div,
"House Price Index (logged)" = m8_nmtc_div
)
# Display model results
modelsummary(models, fmt = 2, stars = c('*' = .05, '**' = .01, '***' = .001), coef_omit = "cbsa", gof_omit = "IC|Log",
notes = list('All models include metro-level fixed effects by core-based statistical area (cbsa).'),
title = paste0("Differences-in-Differences Linear Regression Analysis of NMTC in ", census_division)) %>%
group_tt(j = list("Social Vulnerability" = 2:6, "Economic Outcomes" = 7:9))
| Social Vulnerability | Economic Outcomes | |||||||
|---|---|---|---|---|---|---|---|---|
| SES | HHChar | REM | HOUSETRANSPT | OVERALL | Median Income (USD, logged) | Median Home Value (USD, logged) | House Price Index (logged) | |
| * p < 0.05, ** p < 0.01, *** p < 0.001 | ||||||||
| All models include metro-level fixed effects by core-based statistical area (cbsa). | ||||||||
| (Intercept) | 2.22*** | 2.27*** | 0.44*** | 1.74*** | 6.67*** | 9.87*** | 11.43*** | 4.93*** |
| (0.36) | (0.25) | (0.10) | (0.27) | (0.73) | (0.07) | (0.12) | (0.03) | |
| treat | 0.43** | 0.10 | 0.05 | 0.48*** | 1.06*** | -0.09*** | -0.05 | -0.07 |
| (0.14) | (0.09) | (0.04) | (0.10) | (0.28) | (0.03) | (0.04) | (0.04) | |
| post | -0.07 | -0.04 | -0.01 | 0.03 | -0.10 | 0.00 | -0.05** | 0.61*** |
| (0.05) | (0.04) | (0.01) | (0.04) | (0.10) | (0.01) | (0.02) | (0.01) | |
| treat × post | 0.02 | 0.00 | -0.00 | 0.09 | 0.11 | 0.03 | 0.05 | -0.00 |
| (0.19) | (0.13) | (0.05) | (0.14) | (0.38) | (0.04) | (0.06) | (0.06) | |
| Num.Obs. | 3436 | 3436 | 3436 | 3436 | 3436 | 3436 | 3324 | 1974 |
| R2 | 0.185 | 0.187 | 0.342 | 0.113 | 0.235 | 0.171 | 0.257 | 0.610 |
| R2 Adj. | 0.167 | 0.169 | 0.327 | 0.093 | 0.218 | 0.153 | 0.240 | 0.596 |
| RMSE | 1.41 | 0.99 | 0.41 | 1.05 | 2.87 | 0.27 | 0.45 | 0.30 |
In looking at our social vulnerability index models, we see that there were no categories in the Mountain Division that experienced statistically significant changes in regards to those counties receiving NMTC funding. In particular, we are looking for statistically significant changes in the treat x post variable and none exist in the Mountain Division.
In evaluating the indicators of economic conditions, again we do not see any significantly significant changes in economic outcomes in counties receiving NMTC funding versus those that did not.
Visualize SES
status <- c("NMTC Non-Participant",
"NMTC Participant Counterfactual",
"NMTC Participant",
"NMTC Non-Participant",
"NMTC Participant Counterfactual",
"NMTC Participant")
year <- c(2010,
2010,
2010,
2020,
2020,
2020)
outcome <- c(m1_nmtc_div$coefficients[1],
m1_nmtc_div$coefficients[1] + m1_nmtc_div$coefficients[2],
m1_nmtc_div$coefficients[1] + m1_nmtc_div$coefficients[2],
m1_nmtc_div$coefficients[1] + m1_nmtc_div$coefficients[3],
m1_nmtc_div$coefficients[1] + m1_nmtc_div$coefficients[2] + m1_nmtc_div$coefficients[3],
m1_nmtc_div$coefficients[1] + m1_nmtc_div$coefficients[2] + m1_nmtc_div$coefficients[3] + m1_nmtc_div$coefficients[length(m1_nmtc_div$coefficients)])
svidiv_viz_ses_nmtc <- data.frame(status, year, outcome)
svidiv_viz_ses_nmtc$outcome_label <- round(svidiv_viz_ses_nmtc$outcome, 2)
svidiv_viz_ses_nmtc
## status year outcome outcome_label
## 1 NMTC Non-Participant 2010 2.221420 2.22
## 2 NMTC Participant Counterfactual 2010 2.654338 2.65
## 3 NMTC Participant 2010 2.654338 2.65
## 4 NMTC Non-Participant 2020 2.153580 2.15
## 5 NMTC Participant Counterfactual 2020 2.586499 2.59
## 6 NMTC Participant 2020 2.606719 2.61
slopegraph_plot(svidiv_viz_ses_nmtc, "NMTC Participant", "NMTC Non-Participant","Impact of NMTC Program on SVI SES Flag Count", paste0(census_division, " | 2010 - 2020"))
The slopegraph for SES SVI flags for the NMTC program indicates that in the Mountain Division our NMTC Participant Tracts did not experience a notable decrease in socioeconomic social vulnerability flags in 2020 from the expected count of 2.59 for the counterfactual to 2.61 for the actual outcome.
Because we do not have any statistically significants changes in our outcomes we not need to visualize the counterfactual and outcome graphs. This slopegraph for the SES flag was included for demonstration.
LIHTC Evaluation
Divisional SVI
# Create 2010 df, create post variable and set to 0, create year variable and set to 2010
lihtc_did10_div_svi <- svi_divisional_lihtc_df %>%
select(GEOID_2010_trt, cbsa, F_THEME1_10, F_THEME2_10, F_THEME3_10, F_THEME4_10, F_TOTAL_10, lihtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "lihtc_flag",
"SVI_FLAG_COUNT_SES" = "F_THEME1_10",
"SVI_FLAG_COUNT_HHCHAR" = "F_THEME2_10",
"SVI_FLAG_COUNT_REM" = "F_THEME3_10",
"SVI_FLAG_COUNT_HOUSETRANSPT" = "F_THEME4_10",
"SVI_FLAG_COUNT_OVERALL" = "F_TOTAL_10")
nrow(lihtc_did10_div_svi)
## [1] 202
# Create 2020 df, create post variable and set to 1, create year variable and set to 2020
lihtc_did20_div_svi <- svi_divisional_lihtc_df %>%
select(GEOID_2010_trt, cbsa, F_THEME1_20, F_THEME2_20, F_THEME3_20, F_THEME4_20, F_TOTAL_20, lihtc_flag) %>%
mutate(post = 1,
year = 2020) %>%
rename("treat" = "lihtc_flag",
"SVI_FLAG_COUNT_SES" = "F_THEME1_20",
"SVI_FLAG_COUNT_HHCHAR" = "F_THEME2_20",
"SVI_FLAG_COUNT_REM" = "F_THEME3_20",
"SVI_FLAG_COUNT_HOUSETRANSPT" = "F_THEME4_20",
"SVI_FLAG_COUNT_OVERALL" = "F_TOTAL_20"
)
nrow(lihtc_did20_div_svi)
## [1] 202
lihtc_diff_in_diff_div_svi <- bind_rows(lihtc_did10_div_svi, lihtc_did20_div_svi)
lihtc_diff_in_diff_div_svi <- lihtc_diff_in_diff_div_svi %>% arrange(post, treat, GEOID_2010_trt)
nrow(lihtc_diff_in_diff_div_svi)
## [1] 404
Divisional Median Income
# Create 2010 df, create post variable and set to 0, create year variable and set to 2010, remove any tracts that don't have data for 2010 and 2019
lihtc_did10_div_inc <- svi_divisional_lihtc_df %>%
filter(!is.na(Median_Income_10adj_log)) %>% filter(!is.na(Median_Income_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Income_10adj_log, lihtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "lihtc_flag",
"MEDIAN_INCOME" = "Median_Income_10adj_log")
nrow(lihtc_did10_div_inc)
## [1] 202
# Create 2019 df, create post variable and set to 1, create year variable and set to 2019, remove any tracts that don't have data for 2010 and 2019
lihtc_did19_div_inc <- svi_divisional_lihtc_df %>%
filter(!is.na(Median_Income_10adj_log)) %>% filter(!is.na(Median_Income_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Income_19_log, lihtc_flag) %>%
mutate(post = 1,
year = 2019) %>%
rename("treat" = "lihtc_flag",
"MEDIAN_INCOME" = "Median_Income_19_log")
nrow(lihtc_did19_div_inc)
## [1] 202
lihtc_diff_in_diff_div_inc <- bind_rows(lihtc_did10_div_inc, lihtc_did19_div_inc)
lihtc_diff_in_diff_div_inc <- lihtc_diff_in_diff_div_inc %>% arrange(post, treat, GEOID_2010_trt)
nrow(lihtc_diff_in_diff_div_inc)
## [1] 404
Divisional Median Home Value
lihtc_did10_div_mhv <- svi_divisional_lihtc_df %>%
filter(!is.na(Median_Home_Value_10adj_log)) %>% filter(!is.na(Median_Home_Value_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Home_Value_10adj_log, lihtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "lihtc_flag",
"MEDIAN_HOME_VALUE" = "Median_Home_Value_10adj_log")
nrow(lihtc_did10_div_mhv)
## [1] 187
lihtc_did19_div_mhv <- svi_divisional_lihtc_df %>%
filter(!is.na(Median_Home_Value_10adj_log)) %>% filter(!is.na(Median_Home_Value_19_log)) %>%
select(GEOID_2010_trt, cbsa, Median_Home_Value_19_log, lihtc_flag) %>%
mutate(post = 1,
year = 2019) %>%
rename("treat" = "lihtc_flag",
"MEDIAN_HOME_VALUE" = "Median_Home_Value_19_log")
nrow(lihtc_did19_div_mhv)
## [1] 187
lihtc_diff_in_diff_div_mhv <- bind_rows(lihtc_did10_div_mhv, lihtc_did19_div_mhv)
lihtc_diff_in_diff_div_mhv <- lihtc_diff_in_diff_div_mhv %>% arrange(post, treat, GEOID_2010_trt)
nrow(lihtc_diff_in_diff_div_mhv)
## [1] 374
Divisional House Price Index
lihtc_did10_div_hpi <- svi_divisional_lihtc_df %>%
filter(!is.na(housing_price_index10_log)) %>% filter(!is.na(housing_price_index20_log)) %>%
select(GEOID_2010_trt, cbsa, housing_price_index10_log, lihtc_flag) %>%
mutate(post = 0,
year = 2010) %>%
rename("treat" = "lihtc_flag",
"HOUSE_PRICE_INDEX" = "housing_price_index10_log")
nrow(lihtc_did10_div_hpi)
## [1] 66
lihtc_did20_div_hpi <- svi_divisional_lihtc_df %>%
filter(!is.na(housing_price_index10_log)) %>% filter(!is.na(housing_price_index20_log)) %>%
select(GEOID_2010_trt, cbsa, housing_price_index20_log, lihtc_flag) %>%
mutate(post = 1,
year = 2020) %>%
rename("treat" = "lihtc_flag",
"HOUSE_PRICE_INDEX" = "housing_price_index20_log")
nrow(lihtc_did20_div_hpi)
## [1] 66
lihtc_diff_in_diff_div_hpi <- bind_rows(lihtc_did10_div_hpi, lihtc_did20_div_hpi)
lihtc_diff_in_diff_div_hpi <- lihtc_diff_in_diff_div_hpi %>% arrange(post, treat, GEOID_2010_trt)
nrow(lihtc_diff_in_diff_div_hpi)
## [1] 132
LIHTC Divisional Model
# SVI & Economic Models
m1_lihtc_div <- lm( SVI_FLAG_COUNT_SES ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_svi )
m2_lihtc_div <- lm( SVI_FLAG_COUNT_HHCHAR ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_svi )
m3_lihtc_div <- lm( SVI_FLAG_COUNT_REM ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_svi )
m4_lihtc_div <- lm( SVI_FLAG_COUNT_HOUSETRANSPT ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_svi )
m5_lihtc_div <- lm( SVI_FLAG_COUNT_OVERALL ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_svi)
m6_lihtc_div <- lm( MEDIAN_INCOME ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_inc )
m7_lihtc_div <- lm( MEDIAN_HOME_VALUE ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_mhv )
m8_lihtc_div <- lm( HOUSE_PRICE_INDEX ~ treat + post + treat*post + cbsa, data=lihtc_diff_in_diff_div_hpi )
# Add all models to a list
models <- list(
"SES" = m1_lihtc_div,
"HHChar" = m2_lihtc_div,
"REM" = m3_lihtc_div,
"HOUSETRANSPT" = m4_lihtc_div,
"OVERALL" = m5_lihtc_div,
"Median Income (USD, logged)" = m6_lihtc_div,
"Median Home Value (USD, logged)" = m7_lihtc_div,
"House Price Index (logged)" = m8_lihtc_div
)
# Display model results
modelsummary(models, fmt = 2, stars = c('*' = .05, '**' = .01, '***' = .001), coef_omit = "cbsa", gof_omit = "IC|Log",
notes = list('All models include metro-level fixed effects by core-based statistical area (cbsa).'),
title = paste0("Differences-in-Differences Linear Regression Analysis of LIHTC in ", census_division)) %>%
group_tt(j = list("Social Vulnerability" = 2:6, "Economic Outcomes" = 7:9))
| Social Vulnerability | Economic Outcomes | |||||||
|---|---|---|---|---|---|---|---|---|
| SES | HHChar | REM | HOUSETRANSPT | OVERALL | Median Income (USD, logged) | Median Home Value (USD, logged) | House Price Index (logged) | |
| * p < 0.05, ** p < 0.01, *** p < 0.001 | ||||||||
| All models include metro-level fixed effects by core-based statistical area (cbsa). | ||||||||
| (Intercept) | 3.44*** | 1.87*** | 0.84*** | 1.93*** | 8.09*** | 9.77*** | 11.96*** | 4.84*** |
| (0.19) | (0.18) | (0.06) | (0.17) | (0.38) | (0.07) | (0.08) | (0.09) | |
| treat | -0.05 | 0.10 | -0.05 | -0.06 | -0.05 | 0.11 | 0.07 | 0.20 |
| (0.23) | (0.22) | (0.07) | (0.21) | (0.48) | (0.09) | (0.11) | (0.16) | |
| post | -0.12 | -0.07 | 0.01 | 0.02 | -0.16 | 0.02 | -0.07 | 0.62*** |
| (0.11) | (0.11) | (0.03) | (0.10) | (0.23) | (0.04) | (0.05) | (0.06) | |
| treat × post | -0.26 | -0.06 | -0.01 | 0.19 | -0.13 | 0.04 | 0.04 | 0.03 |
| (0.31) | (0.30) | (0.10) | (0.28) | (0.64) | (0.12) | (0.15) | (0.20) | |
| Num.Obs. | 372 | 372 | 372 | 372 | 372 | 372 | 342 | 126 |
| R2 | 0.255 | 0.434 | 0.589 | 0.197 | 0.421 | 0.325 | 0.479 | 0.655 |
| R2 Adj. | 0.168 | 0.367 | 0.541 | 0.102 | 0.353 | 0.246 | 0.411 | 0.577 |
| RMSE | 0.95 | 0.90 | 0.30 | 0.87 | 1.95 | 0.36 | 0.42 | 0.30 |
As with our national data, we do not see a statistically significant changes in social vulnerability or economic outcomes for tracts participating in the LIHTC program. We cannot conclude that the program had a measurable impact in the Mountain Division tracts.
Visualize Divisional Models
Because we do not have any statistically significant changes in our outcomes we not need to visualize the counterfactual and outcome slopegraphs.